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The purpose of this paper is to examine a multidimensional model of marketing culture and performance in tourism restaurants operating in Jordan. The paper introduces a model proposing certain associations between Webster’s (1990) marketing culture dimensions and attempts to underline how such associations affect restaurants’ performance.

A structured and self-administered survey was used, targeting managers and employees of tourism restaurants operating in Jordan. A sample of 334 tourism restaurants’ managers and employees were involved in the survey. A series of exploratory and confirmatory factor analyses were used to assess the research constructs dimensions, unidimensionality, validity and composite reliability. Structural path model analysis was also used to test the hypothesised interrelationships of the research model.

The empirical findings indicate that the marketing culture dimensions are seven rather than six, as proposed by Webster’s (1990) original model: service quality, interpersonal relationships, management–front-line interaction, selling task, organisation, internal communication and innovativeness. “Organisation” had positively and significantly affected “interpersonal relationships”. “Interpersonal relationships” had positively and significantly affected each of “management–front-line interaction”, “selling task” and “internal communications”. On the other hand, each of “management–front-line interaction”, “selling task” and “internal communications” had positively and significantly affected “innovativeness”. However, “innovativeness” itself had positively and significantly affected each of “service quality” and restaurant performance. Finally, “service quality” had positively and significantly affected restaurants’ performance.

Only seven dimensions of marketing culture were examined; meanwhile, there could also be other dimensions that affect restaurants’ performance. This paper has also examined the effect of a multidimensional model of marketing culture on restaurants’ financial performance only; the use of other types of non-financial measures could yield different results. The fact that paper’s sample consisted only of Jordanian restaurants further limits its generalisation potential.

The paper reinforces the importance of sound marketing culture to Jordanian tourism restaurants. It further underlines the importance of several marketing culture dimensions, particularly those related to employees’ selection, development and communication. Further, the paper emphasises the particular importance of front-office employees to the success of Jordanian restaurants. Tourism restaurants’ managers and executives can benefit from such findings for designing their marketing culture strategies to achieve long-term performance objectives.

This paper represents the first empirical attempt to examine the interrelationships between marketing culture dimensions introduced by Webster (1990). Accordingly, it should shed more light on the dynamics of marketing culture within service organisations, and how such dynamics affect organisations’ performance. Further, the paper is the first of its kind to study marketing culture dynamics in the context of Jordanian tourism restaurants industry. International tourism restaurants planning to expand their operations in Jordan’s tourism industry have now valuable empirical evidence concerning the marketing culture dimensions and their effect on performance.

To set up the analytical model of reaction wheel assembly (RWA) by using the other theory and to provide a new method to identify the parameters of the empirical model of RWA.

Setting up the analytical model of RWA using virtual work theory, and presents the energy compensation method. The energy compensation method to improve the computation accuracy of amplitude coefficients of the empirical model of RWA. In the empirical model of RWA, the assumption is that the disturbances consist of discrete harmonics, and the amplitudes is proportion to the square of the wheel speed.

The errors of amplitude coefficients adopting energy compensation window excel the amplitude spectrum method. The energy compensation method improves the parameters identification accuracy, and provides a new method to set up more accurate empirical disturbance model of RWA.

Providing a valuable identification method of amplitude coefficients of the empirical model of RWA, and improving the accuracy of identification.

Putting forward up the method of energy compensation to identify the amplitude coefficients of the empirical model of RWA, and improving the accuracy. This method is simple, practical for the system design.

This paper aims to study the determinants of private investment in Egypt while accounting for uncertainty associated with financing decisions of the firm using time series analysis over the period 1982-2015. The analysis is based on Tobin’s (1969) Q-theory of investment. The variables used in the empirical model are investment rate, average q index, prices of capital goods, internal finance and external finance.

This research is concerned with the model specification of a dynamic Average Q model. In that respect, the current research describes the data, presents the empirical methodology and estimates the Average Q model of investment and obtains the results. The empirical procedures and results of studying the average Q model. It includes testing for the unit root in the time series, vector error correction model (VECM) and cointegration long run analysis, and finally estimations of the model under uncertainty and empirical results.

Stochastic shocks to the determinants of private investment in Egypt have their impact on investment rate. The representation of impulse response in VECM shows that a one standard deviation shock to the value of the firm has a positive impact on investment rate. Stochastic shocks to both internal finance and external finance have slightly positive response from investment rate. Also, a stochastic shock to investment rate has a positive yet declining response from itself. However, a stochastic shock to prices of capital goods has a negative impact on investment rate. The representation of variance decomposition in VECM shows that investment rate is positively affected yet at a declining rate by a one standard deviation shock in both internal and external finance during the period 1982-2015. Also, a stochastic shock in the value of the firm or in the prices of capital goods has a slightly positive impact on investment rate.

Investment and capital accumulation are the main vehicles for economic growth and development. There have been fluctuations in Egypt’s investment rates since mid-1970s due to variations in saving rates. Thus, it is important to present some policy implications that could potentially assist the enhancement of the Egyptian economy. In that respect, the estimated results of the empirical model show that changes in the prices of capital goods in Egypt are significant factors that have negative impact on investment rate. Prices of imported capital goods in Egypt are affected by foreign exchange market conditions in the form of significant changes in the pound exchange rate. Thus, foreign exchange market reforms, as adopted recently in the Egyptian economy and improvements in trade balance, are important steps to alleviate obstacles that hinder investment. Regarding the source of finance, the estimated results showed that changes in both internal and external finance have a positive impact on investment rate. In this case, it is the firm’s decision to choose the method of financing its investment depending on factors such as its market value, institutional size and capacity and the opportunity cost of the funds used in financing the required investment.

Much of what we learn from empirical research is based on a specific empirical model(s) presented in the literature. However, the range of plausible models given the data is potentially larger, thus creating an additional source of uncertainty termed: model uncertainty. The purpose of this paper is to examine the effect of model uncertainty on empirical research in HRM and suggest potential solutions to deal with the same.

Using a sample of call center employees from India, the authors test the robustness of predictors of intention to leave based on the unfolding model proposed by Harman et.al. (2007). Methodologically, the authors use Bayesian Model Averaging (BMA) to identify the specific variables within the unfolding model that have a robust relationship with turnover intentions after accounting for model uncertainty.

The findings show that indeed model uncertainty can impact what we learn from empirical studies. More specifically, in the context of the sample, using four plausible model specifications, the authors show that the conclusions can vary depending on which model the authors choose to interpret. Furthermore, using BMA, the authors find that only two variables, job satisfaction and perceived organizational support, are model specification independent robust predictors of intention to leave.

The research has specific implications for the development of HR analytics and informs managers on which are the most robust elements affecting attrition.

While empirical research typically acknowledges and corrects for the presence of sampling uncertainty through p-values, rarely does it acknowledge the presence of model uncertainty (which variables to include in a model). To the best of the authors’ knowledge, it is the first study to show the effect and offer a solution to studying total uncertainty (sampling uncertainty + model uncertainty) on empirical research in HRM. The work should open more doors toward more studies evaluating the robustness of key HRM constructs in explaining important work-related outcomes.

The main aim of this paper is to verify whether the modern mainstream economic theory of multinational enterprise that explains foreign direct investment (FDI) from developed countries is also able to account for investment decisions of multinational enterprises (MNEs) from emerging economies.

Using Knowledge-And-Physical-Capital (KAPC) model as an analytical framework and Poisson-pseudo maximum likelihood estimation technique, the authors identify determinants of FDI flows from emerging economies. The data set consists of 38 home and 134 host countries during the period 2000–2012. Empirical evidence supports high explanatory power of KAPC model. Further, compared with the earlier Knowledge-Capital (KC) model, results confirm the importance of physical capital.

The estimation results confirm the hypothesis that mainstream economic theory can explain FDI flows from the emerging economies by highlighting the roles of total market size, skilled-labor abundance, investment and trade costs and geographical distance between two countries.

This study casts doubt on the alternative way that the KAPC model suggests to distinguish between horizontal and vertical FDI. The argument that horizontal MNE headquarters would be relatively more abundant than vertical MNE headquarters in countries that are abundant in physical capital relative to skilled labor seems reasonable but the idea of variable specification in the estimated equation should be revised.

Firms should be allowed to move their resources freely into and out of specific activities, both internally and internationally across border. To reach that goal, governments of potential host countries can adopt several measures, most importantly remove restrictions on payments, transfers and capital transactions and open previously closed industries to welcome foreign investment. In addition, to improve investment climate in general, governments need to pay attention to enhancing security of property rights, regulating internal taxation (i.e. corporate income tax), guaranteeing adequacy of infrastructure, efficient functioning of finance and labor markets and fighting against corruption.

The location choice of emerging investors set priority on similarity in economic size, geographical and cultural proximity. It is because shared borders or common official languages would reduce information costs and enhance information flows. Also, investors consider horizontal FDI (with motivation to expand market demand) as one of main modes of entry into a foreign market and a substitute for export. Likewise, distance is often understood as an important investment friction.

The outstanding contribution is that the research has uncovered the positive and statistically significant effect of physical capital on FDI activity, which has not been discussed in the earlier KC model. However, at the same time, the study casts doubt on the KAPC model's argument that relative abundance in physical capital to skilled labor between two countries determines FDI types and suggests that this argument and its empirical model specification should be carefully reviewed.

A comprehensive and computationally efficient modeling strategy for the rapid and accurate simulation of implanted impurity distribution profiles in single‐crystal silicon has been developed. This modeling strategy exploits the advantages of both Monte Carlo simulation and semi‐empirical models by combining the two approaches in a complementary manner. The dual Pearson semi‐empirical model is used to accurately and efficiently model the dose and implant angle dependence of impurity profiles as well as the dependence on energy. This new comprehensive model allows convenient and accurate simulation of implanted boron distribution profiles in single‐crystal silicon as a function of dose, tilt angle, and rotation angle, in addition to ion energy, and it has been demonstrated by implementation in the process simulation code SUPREM III.

This chapter is designed to outline how current methods in formal policy analysis have evolved to better respect limits to an analyst's knowledge. These limits are referred to as model uncertainty both in order to capture the idea that formal policy analysis is predicated on mathematically precise formulations that embody assumptions on the part of an analyst and because model uncertainty, which represents a recognition of the potential for these assumptions to produce unsound analyses, has been an active area of research in economics and statistics for the last 15 or so years. The argumentation in this chapter is not original and is admittedly selective. For Austrian economists, the paper will hopefully be of interest in indicating how empirical work is evolving in a way that better respects limits to a social scientist's knowledge. I certainly do not mean to suggest that these arguments should eliminate the objections that have been raised by some Austrian economists to formal empirical work. Rather, the intent of this chapter is to indicate the possibility of dialog and debate between Austrian and non-Austrian economists on the role of formal empirical work. In several contexts, I have introduced arguments concerning the limits of formal econometric analysis by Hayek and von Mises to both illustrate how the perspectives in this chapter relate to their views in order to suggest why, in my judgment, some of their skepticism is unwarranted.

This paper surveys the treatment of expectations in estimated Dynamic Stochastic General Equilibrium (DSGE) macroeconomic models.

A recent notable development in the empirical macroeconomics literature has been the rapid growth of papers that build structural models, which include a number of frictions and shocks, and which are confronted with the data using sophisticated full-information econometric approaches, often using Bayesian methods.

A widespread assumption in these estimated models, as in most of the macroeconomic literature in general, is that economic agents' expectations are formed according to the Rational Expectations Hypothesis (REH). Various alternative ways to model the formation of expectations have, however, emerged: some are simple refinements that maintain the REH, but change the information structure along different dimensions, while others imply more significant departures from rational expectations.

I review here the modeling of the expectation formation process and discuss related econometric issues in current structural macroeconomic models. The discussion includes benchmark models assuming rational expectations, extensions based on allowing for sunspots, news, sticky information, as well as models that abandon the REH to use learning, heuristics, or subjective expectations.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

The current study conceptualizes and empirically tests a new model of market brand equity (MBE). This model, that not just provides an understanding of customer mindsets toward the brand, as most empirical models do, but also measures the marketing benefits of such mindsets. The present study offers two models. One is comprehensive and theoretical while the other is an empirical model. The empirical model is a practical model drawn from the more comprehensive and conceptualized model. The hypothesized empirical MBE model is tested using structural equation modeling (SEM) analysis followed by a formula that offers a method to calculate and rank competitive brands in the market place. The purpose of this paper is to conclude with a discussion of the implications of the model.

The findings of the present research are based on a representative sample of 964 cellular phone users selected randomly from an Israeli internet panel were analyzed. The questions related to the dimensions of the brand equity needed a more intimate relationship of the customers with the brand. Thus, those questions were asked only with regard to the brand that the respondents were mainly using. These questions were concerned with brand knowledge, brand commitment and brand overall attitude. The other questions that the respondents answered were about three other brands on the market. All dimensions, except purchase barriers, were measured on a ten-point scale.

SEM analysis was used to test the hypothesized MBE model as well as alternative models. The results, which supported the hypothesized model, indicated that knowledge has a strong positive effect on image, personality and attitude. Image has a positive effect on attitude, but that of personality was insignificant. Attitude, image and personality have a positive effect on commitment. Commitment affects recommendation strongly and positively. Both commitment and recommendation have a positive and significant effect on potential market share.

The limitations of the current research are that it was not measured over time and that only one product category has been tested. In addition to dealing with these limitations, future research may also add additional marketing performance outcome variables such as the ability to obtain premium prices and to exercise brand power in relation to channels of distribution.

The model presented in this paper provides the marketer with the ability to compare, from a competitive perspective, the relative average in the market place of customer mindset, customer performance and marketing performance. The analysis also reveals whether to invest in strengthening customer mindset or in capturing a greater market share. When the brand leader is far from its followers, an additional analysis may be required and it may be necessary to increase the sensitivity of the analysis by examining separately (without the leading brand) the relative differences between the follower brands. Moreover, the measurement questions should be adjusted to fit different product categories. For example, in testing the MBE in the service industry, “product performance,” which is a component of brand commitment, should be measured by the “quality of service.” But the way of using the model will not change. Another example for future research may be found in sport marketing, such as among football or basketball clubs. In such instances, performance – winning or losing – or even the quality of the players on the team may be considered. It is suggested here that the MBE’s measurement of fast-moving products vs slow moving ones. However, in such cases the model would probably show a significant difference in involvement with the brands of fast-moving products displaying much lower customers’ involvement then brands of slow-moving products.

The empirical model suggested in this study is a new and practical market-based brand equity that uses commitment as the main construct, building brand equity to represent the performance outcome of the customer mindset used in the models noted above. The current study also offers a new practical and useful formula for calculating and ranking MBE.