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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.

The purpose of this paper is to examine the impacts of fiscal policy, namely, net tax and government expenditure on national saving and its nonlinearity. The author first investigates whether the impacts of fiscal policy on national saving have changed after the global financial crisis of 2008. Then, the author tests the nonlinearity of the relationship by taking account of the economic cycle, namely, economic expansion (boom) and economic recession (bust).

The empirical model bases on a reduced-form equation with national saving as a dependent variable, lagged value of national saving, output gap and fiscal policy as independent variables. The two-step system GMM approach was employed to estimate the empirical model, using a panel of 23 emerging Asian economies in the period of 1990-2015.

The empirical results show that tax policy and expenditure policy follow the predictions of the overlapping generation model with finite horizon and the Keynesian view. The nonlinearity of fiscal policy is twofold. The conduct of fiscal policy in the period after 2008 seems effective, while the effect is insignificant in the period before 2008. Likewise, fiscal policy tends to have more significant effects in bust cycle. The effect of tax policy is increased during recession, while the effect of government spending is more pronounced during economic downturn.

The contributions of this paper are twofold. First, it is shown that fiscal policies in the region had more impacts on national saving after the global financial crisis of 2008. Second, the research confirms nonlinear impact of fiscal policy on saving behavior during economic recession and economic boom.

From the organisational perspective, the authors know that management, including innovation management, becomes less “organised” by bureaucracy and administrative tools, and much more impacted by organisational capabilities, competences and hidden, “soft” routines, bringing innovation and creativity to the core of organisation. The purpose of this paper is to focus on competency sets for open innovation (OI) and is to provide recommendations for OI competency development in companies, linked to the core OI processes.

The research is exploratory and aims at theory-based practical indication combining deductive identification of competency clusters and inductive model development. Thus, the authors apply quantitative methods to data collection and analysis. The authors conducted an extensive literature review on competence challenges with regard to execution of OI, and empirical data analysis based on a large-scale structured industrial survey in Europe (N=264), leading to the development of competency sets for companies. SPSS tools are applied for empirical tests.

The authors develop a generic OI competency model applicable across industries, combined with organisational implications for sustaining OI management capabilities. The research clusters competencies based on the empirical analysis, which addresses the various challenges of OI, leading to recommendations for competency management in an OI context.

The data were collected from one key informant per company. Although the authors made efforts to ensure that this was a senior manager responsible for innovation, the authors cannot exclude some bias in the way that OI activities and related competencies are perceived. Exploratory nature of the research, which calls for a more systematic investigation of the OI activity modes and the OI competencies resulting competency model. In particular, the competencies could be tested on an inter-professional sample of employees with involvement in and/or responsibility for innovation, development, and HR management, as well as on leaders of innovating companies. Third, although significant in size for the analyses undertaken, the sample is not large enough to enable a more fine-tuned analysis of regional differences across Europe in the way that OI is managed through the development and implementation of competencies.

The research contributes to the OI management field with an outlined OI competency profile that can be implemented flexibly and tailored to individual firm’s needs. It brings indications for both further theory building and practice of innovation organisation, especially with regard to human resource development and organisational capability building for OI.

The social implications of the paper result from the contribution to innovation management competency development in OI regimes, which is an important tool for designing contemporary educational programmes, contributes to OI management sophistication in business which is especially important during the economy slowdown and search for new sources of growth and productivity, and supports firms productive engagement in OI ecosystems and collective technology upgrading towards higher societal benefits and stakeholder involvement.

An empirically grounded OI competency model is proposed with an implication to support human resource development for OI. To the best of the authors’ knowledge, there has been no prior attempt to build such a model. The distinguished feature of the research is its extensive European coverage of 35 countries and multinational scope. The empirical validation strategy makes the research extremely relevant for management decisions related to human factors related OI capability development in organisations.

As technology in tourism and hospitality (TTH) develops technical artifacts according to visitors’ demands, it must deal with both behavioral and design constructs in the context of structural equation modeling (SEM). While behavioral constructs are typically modeled as common factors, the study at hand introduces the composite into TTH to model artifacts. To deal with both kinds of constructs, this paper aims to exploit partial least squares path modeling (PLS-PM) as a confirmatory approach to estimate models containing common factors and composites.

The study at hand presents PLS-PM in its current form, i.e. as a full-fledged approach for confirmatory purposes. By introducing the composite to model artifacts, TTH scholars can use PLS-PM to answer research questions of the type “Is artifact xyz useful?”, contributing to a further understanding of TTH. To demonstrate the composite model, an empirical example is used.

PLS-PM is a promising approach when the model contains both common factors and composites. By applying the test for overall model fit, empirical evidence can be obtained for latent variables and artifacts. In doing so, researchers can statistically test whether a developed artifact is useful.

To the best of the authors’ knowledge, this is the first study to discuss the practical application of composite and common factor models in TTH research. Besides introducing the composite to model artifacts, the study at hand also guides scholars in the assessment of PLS-PM results.

因为旅游酒店科技（TTH）根据游客需求而定制科技产品, TTH必须在结构方程模型（SEM）下结合游客行为和设计等变量。一般行为变量在模型中是常见因子, 本研究将这些变量编入TTH结构成为模块。本研究采用PLS-PM方法来预估含有隐性变量和模块的模型。.

本研究设计PLS-PM模式, 即确定性全变量方法。TTH学者们通过引进结构形成模型模块, 使用PLS-PM研究方法, 以回答研究问题“模块xyz有用吗？”, 因此对TTH进一步理解。为了展示复合模型, 本论文采用实际验证。.

PLS-PM在面对模块内存在常见因子和复合模块的结构时是有力方法。实际验证结果通过整体最佳模型参数, 得到隐性变量和模块。为此, 研究者们能够在统计方法上测量是否开发的模型模块是否有用。.

据作者所知, 本论文是首个研究在TTH领域上应用模块和常见因子模型。本研究引进显性变量在模型模块中, 以指导学者评估PLS-PM结果报告。.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

Any finance models must specify the market prices of risk that determines the relationship between the two probability measures. Although the general form of the change of measure is well known, few papers have investigated the change of measure for interest rate models and their implications for the way a model can fit to empirical facts about the behaviour of interest rates. This paper demonstrates that arbitrary specifications of market price of risk in empirical studies under the two factor affine interest rate model with jumps are not compatible with the theory of original interest rate model. Particularly, the empirical models of Duffee (2002) and Duarte (2003) may be wrong specifications in some parts under a rigorous theoretical interest rate theory.

This study aims to propose a semiempirical and semitheoretical cyclic compaction constitutive model of coarse-grained soil filler for the high-speed railway (HSR) subgrade under cyclic load.

According to the basic framework of critical state soil mechanics and in view of the characteristics of the coarse-grained soil filler for the HSR subgrade to bear the train vibration load repeatedly for a long time, the hyperbolic empirical relationship between particle breakage and plastic work was derived. Considering the influence of cyclic vibration time and stress ratio, the particle breakage correction function of coarse-grained soil filler for the HSR subgrade under cyclic load was proposed. According to the classical theory of plastic mechanics, the shearing dilatation equation of the coarse-grained soil filler for the HSR subgrade considering particle breakage was modified and obtained. A semiempirical and semitheoretical cyclic compaction constitutive model of coarse-grained soil filler for the HSR subgrade under cyclic load was further established. The backward Euler method was used to discretize the constitutive equation, build a numerical algorithm of “elastic prediction and plastic modification” and make a secondary development of the program to solve the cyclic compaction model.

Through the comparison with the result of laboratory triaxial test under the cyclic loading of coarse-grained soil filler for the HSR subgrade, the accuracy and applicability of the cyclic compaction model were verified. Results show that the model can accurately predict the cumulative deformation characteristics of coarse-grained soil filler for the HSR subgrade under the train vibration loading repeatedly for a long time. It considers the effects of particle breakage and stress ratio, which can be used to calculate and analyze the stress and deformation evolution law of the subgrade structure for HSR.

The research can provide a simple and practical method for calculating deformation of railway under cyclic loading.

The results of this study have significant policy implications for charting a new course toward enhancing agricultural productivity among Chinese farmers.

By establishing a rural household decision-making model based on the transfer market of farmland operation rights, this paper systematically analyzes the effects of land transfer-in and land transfer-out on the productivity (per labor income) of rural households. The authors conducted basic regression analysis and robustness tests using propensity score-matching and proxy variable approaches based on the micro survey data from rural households in 30 counties in 21 provinces/municipalities/autonomous regions in 2013.

After the completion of land transfer, the total productivity of rural households transferring in lands will increase with an increase in the agricultural productivity; the total productivity of rural households transferring out land will increase due to a rise in non-agricultural productivity and the absolute total productivity of rural households not involved in land transfer will remain unchanged.

Unlike previous literature, this paper discusses the impacts of land transfer-in and transfer-out on total productivity, agricultural productivity and non-agricultural productivity among various rural households (i.e. those transferring in land, transferring out land or which are self-sufficient).

The COVID-19 pandemic has forced countries to consider how to reach vulnerable communities with extended outreach services to improve vaccination uptake. The authors created an optimization model to align with decision-makers' objective to maximize immunization coverage within constrained budgets and deploy resources considering empirical data and endogenous demand.

A mixed integer program (MIP) determines the location of outreach sites and the resource deployment across health centers and outreach sites. The authors validated the model and evaluated the approach in consultation with UNICEF using a case study from The Gambia.

Results in The Gambia showed that by opening new outreach sites and optimizing resource allocation and scheduling, the Ministry of Health could increase immunization coverage from 91.0 to 97.1% under the same budget. Case study solutions informed managerial insights to drive gains in vaccine coverage even without the application of sophisticated tools.

The research extended resource constrained LMIC vaccine distribution modeling literature in two ways: first, endogenous calculation of demand as a function of distance to health facility location enabled the effective design of the vaccine network around convenience to the community and second, the model's resource bundle concept more accurately and flexibly represented complex requirements and costs for specific resources, which facilitated buy-in from stakeholders responsible for managing health budgets. The paper also demonstrated how to leverage empirical research and spatial analysis of publicly available demographic and geographic data to effectively represent important contextual factors.

Many important constructs of business and social sciences are conceptualized as composites of common factors, i.e. as second-order constructs composed of reflectively measured first-order constructs. Current approaches to model this type of second-order construct provide inconsistent estimates and lack a model test that helps assess the existence and/or usefulness of a second-order construct. The purpose of this paper is to present a novel three-stage approach to model, estimate, and test second-order constructs composed of reflectively measured first-order constructs.

The authors compare the efficacy of the proposed three-stage approach with that of the dominant extant approaches, i.e. the repeated indicator approach, the two-stage approach, and the hybrid approach by means of simulated data whose underlying population model is known. Moreover, the authors apply the three-stage approach to a real research setting in business research.

The study based on simulated data illustrates that the three-stage approach is Fisher-consistent, whereas the dominant extant approaches are not. The study based on real data shows that the three-stage approach is meaningfully applicable in typical research settings of business research. Its results can differ substantially from those of the extant approaches.

Analysts aiming at modeling composites of common factors should apply the proposed procedure in order to test the existence and/or usefulness of a second-order construct and to obtain consistent estimates.

The three-stage approach is the only consistent approach for modeling, estimating, and testing composite second-order constructs made up of reflectively measured first-order constructs.