The integration-responsiveness framework and subsidiary management: A commentary

This commentary article discusses the appropriateness of using the integration-responsiveness framework for studying subsidiary management. The framework is frequently used and highly accepted in the international business literature, but the research contributions of applying the framework can be questioned. This commentary article discusses the applicability of the framework from a theoretical point of view, and furthermore, argues that it is difficult to empirically test subsidiary strategies and management based on hypotheses derived from the framework, and that the implications that can be drawn have limited theoretical content.     

A Note on the Use of Survey Research Firms to Enable Empirical Data Collection

This forward thinking article examines the risks and rewards of using survey research firms to enable empirical data collection, and issues a cautionary note about its application. An exposition and discussion of this form of data collection in supply chain management is relevant today, due to the “survey‐fatigue” among the population of business professionals from whom we seek a response. While this approach has some history in other disciplines, it is still relatively new among supply chain management researchers. To help supply chain management scholars assess the appropriateness of this type of data collection method, this forward thinking article provides invaluable guidance as derived from the authors' recent experiences with the approach. As such, we share our observations and lessons learned. The conclusion is that the use of survey research firms for empirical data collection can be a viable, alternative approach to self‐administered surveys. However, care should be taken in its application.     

Partner Symmetries,Partner Conflict and the Quality of Joint Venture Marketing Strategy: An Empirical Investigation

Joint venture research has overlooked the potential impact of partner conflict on the quality of joint venture marketing strategy. We address this issue by developing formal hypotheses concerning the antecedents to and consequences of functional and dysfunctional conflict between joint venture parent organisations on joint venture marketing strategy. We then describe an empirical examination of our model. Data collection was undertaken via a mail survey of New Zealand joint venture companies. Forty usable responses were returned, corresponding to a response rate of twenty-five percent. Correlation analysis of the data indicates that the degree to which partners exhibit both functional and dysfunctional conflict is influenced by (a) the degree to which joint venture partners share strategic and operational fit, (b) partners' level of mutual commitment, (c) levels of mutual trust, (d) opportunistic behaviours and (e) the adoption of collaborative communication approaches. Furthermore, both functional and dysfunctional partner conflict appear to significantly influence the quality of joint ventures' marketing strategy formulation and implementation. We discuss the managerial implications forthcoming from these results.     

How Transdisciplinarity Can Help to Improve Operations Research on Sustainable Supply Chains—A Transdisciplinary Modeling Framework

We present a transdisciplinary modeling framework that enhances collaborative research on sustainable supply chain management (SSCM). Decision support concerning such systems is commonly provided using operations research (OR) methodologies. The quality of respective models depends on the appropriateness of both mathematical representation of the focal system and data input. Concerning this matter, OR faces severe criticism as groundwork is commonly neglected. This results in a lack of holistic understanding and in insufficient modeling of real‐world problems. Crucial characteristics of the underlying system are often over simplified due to single‐discipline assessments. Particularly, in the context of complex sustainability challenges, multiple nonacademic competencies and expertise are required. Although latest research indicates that collaborative research settings are highly beneficial regarding SSCM, a dearth of integration between disciplines exists. Therefore, we develop a conceptual framework that helps to overcome these shortcomings based on the paradigm of transdisciplinary research (TDR), which needs substantiation to enhance collaboration and to ensure applicability. Accordingly, we propose appropriate methodologies for each step within the framework. Overall, the framework enables holistic analysis of a focal system by providing a sound approach for SSCM‐oriented TDR projects. The value of the framework is eventually demonstrated by two cases that deal with SSCM issues.     

Currency crises, sunspots and Markov-switching regimes

This paper investigates the theoretical properties of a class of escape clause models of currency crises as well as their applicability to empirical work. We show that under some conditions these models give rise to an arbitrarily large number of equilibria, as well as cyclic or chaotic dynamics for the devaluation expectations. We then propose an econometric technique, based on the Markov-switching regimes framework, by which these models can be brought to the data. We illustrate this empirical approach by studying the experience of the French franc between 1987 and 1993, and find that the model performs significantly better when it allows the devaluation expectations to be influenced by sunspots.     

Purchasing Competence: A Stakeholder‐Based Framework for Chief Purchasing Officers

A specific research stream within the purchasing and supply management literature focuses on the development of purchasing competence frameworks. We apply stakeholder theory and multiple methods of data collection to develop and confirm a hierarchy‐specific purchasing competence management framework for Chief Purchasing Officers and validate it using confirmatory factor analysis on empirical data from 124 multinational companies. The results reveal a significant relationship between Chief Purchasing Officers purchasing management competence and different purchasing performance measures confirming the appropriateness of stakeholder theory for such a competence framework.     

Flexible covariance dynamics,high-frequency data,and optimal futures hedging

This paper investigates the out-of-sample performance of hedged portfolios constructed using a novel rotated ARCH (RARCH) model class, which enables flexible covariance dynamics for spot and futures returns. The model's empirical fit can be significantly improved when it incorporates rotated realized covariance matrix measures. The empirical results suggest that a highly risk-averse hedger implementing the restricted RARCH model would be willing to pay substantial switching fees to capture the incremental gains generated by the flexible and informative alternative; this thus supports the economic importance of incorporating high-frequency data into flexible RARCH modeling processes for the construction of optimal hedged portfolios.     

Counting your customers from an ��always a share�� perspective

Models based on the Pareto/NBD framework are among the most popular for customer base analysis. The Pareto/NBD framework assumes that purchasing follows a Poisson process until the customers defect. Therefore, models based on this framework may systematically underestimate the number of future transactions from customers whose probability of returning is greater than zero. In this paper, we propose a new model which assumes that customers do not defect, but instead switch freely between an active and an inactive state. We call this model the ??interrupted Poisson process??. According to the model, customers purchase through a Poisson process when they are active and they do not purchase when they are inactive. Bayesian simulation methods for parameter estimation are developed and implemented via a Markov chain Monte Cacrlo (MCMC) simulation. Several useful expressions for customer base analysis are derived. Through simulation experiments, we show that the rate of customers moving from an inactive to an active state is an important factor determining the fit and predictive ability of the Pareto/NBD model and our model. An empirical analysis, using two real-life datasets, demonstrates the superior performance of the proposed model.     

营销动态能力的概念与量表开发

营销动态能力是动态能力在企业营销领域的特定形式,对其内涵及结构维度的研究还比较缺乏。文章运用混合方法对营销动态能力进行概念界定与量表开发：首先对营销动态能力理论渊源进行梳理,然后对其概念内涵进行界定;继而通过内容分析和探索性因子分析编制营销动态能力量表;最后运用327家样本企业数据对量表进行信度和效度检验。结论表明,营销动态能力具有多维度结构,包含市场感知能力、界面协同能力和顾客响应能力三大维度。研究结论为企业培育营销动态能力提供方向指引,也为后续实证研究奠定工具基础。     

Targeting Firm Births and Economic Regeneration in a Lagging Region

This paper provides a critical evaluation of the practice of targeting the firm birth rate as part of a regional regeneration policy. It raises some fundamental questions about the appropriateness of such a practice and shows that different specifications of the birth rate generate very different implications for policy intervention, as measured by the number of births required. It also demonstrates that even when the specification is agreed, the translation of the target into actual numbers of births is far from straightforward, especially where the target aspires to match a region’s performance with what is going on elsewhere and where the survival rate of businesses is also being targeted in parallel. The North East of England is used as the particular context for the evaluation, although the discussion has much wider applicability.     

Sponsorship portfolio as brand image creation strategies: A commentary essay

This essay discusses Chien, Cornwell, and Pappu's (forthcoming) paper, “Sponsorship portfolio as brand image creation strategy.” Although Chien et al. (forthcoming) seek to enhance understanding of the impact of a brand's sponsorship portfolio on its brand image they are not completely successful in this endeavor. One of their key constructs, the event personality fit (EPF) construct, has no significant effect on brand meaning. This essay suggests that this finding is because of limitations in the brand personality metrics in the study and because of the tautological nature of the hypotheses proposals. Their sponsorship category relatedness (SCR) construct, however, is a useful construct for those seeking to assemble a portfolio of sponsored products that builds positive brand meaning for the sponsor's brand.     

Corporate social responsibility in emerging economies: Investigating firm behavior in the Indian context

Scholars have questioned the appropriateness of using a western‐centric framework to investigate corporate social responsibility (CSR) in emerging economies. This study assesses the appropriateness of using such a framework in one emerging economy—India. More specifically, the drivers of CSR and their impact on firm‐level CSR activity in the Indian context are investigated and compared with those in developed economies. Content analysis of 369 CSR policy statements of publicly traded Indian firms revealed the factors that drive CSR activities of Indian firms are similar to those found in developed economies. However, the ways firms respond to the drivers of CSR are surprisingly different in the Indian context, and these differences can be traced to attributes of the Indian socio‐cultural context. Implications and recommendations for future research conducted in India, and in other emerging economies, are offered.     

Volatility and growth in developing economies: some numerical results and empirical evidence

This paper analyzes the effect of volatility on growth in a developing economy facing an imperfect world capital market. The analysis comprises: (i) the development of a formal framework for assessing the role of risk on growth; (ii) numerical simulation; and (iii) empirical testing of the model, using data from 61 developing economies. We find that the model plausibly replicates the equilibrium of small stylized economies subject to external and internal sources of risk. We define a benchmark economy and study the effects of various sources of risk and borrowing costs on the equilibrium growth rate, its variability, and welfare. The numerical results obtained are intuitive and supported by empirical evidence.     

Bayesian estimation of an open economy DSGE model with incomplete pass-through

In this paper, we develop a dynamic stochastic general equilibrium (DSGE) model for an open economy, and estimate it on Euro area data using Bayesian estimation techniques. The model incorporates several open economy features, as well as a number of nominal and real frictions that have proven to be important for the empirical fit of closed economy models. The paper offers: i) a theoretical development of the standard DSGE model into an open economy setting, ii) Bayesian estimation of the model, including assessments of the relative importance of various shocks and frictions for explaining the dynamic development of an open economy, and iii) an evaluation of the model's empirical properties using standard validation methods.     

Constructing conceptual models for knowledge capture and delivery systems

Appropriate conceptualization of the nature of entities and relationships in a problem domain is a key prerequisite to the successful design of computerized decision aids for business, especially those developed for more than one idiosyncratic user. The need for a reliable conceptual model is particularly acute in the design of decision support systems that must function in problem‐solving situations with no existing theoretical framework or where theory and practice differ considerably.

This paper presents an interative procedure for developing a reliable conceptual model by testing the “fit”; of successive revisions of the model against a collection of “think‐aloud”; verbal problem‐solving protocols of people with experience in the domain. The model is revised each time until it is verifiably and consistently accurate. Such a procedure, it is argued, is more objective and reliable than intuition or traditional knowledge engineering and requires considerably less experimental data collection and analysis than more elaborate empirical model development procedures.

The feasibility of this procedure is illustrated by using it to construct a conceptual model for a computer‐based system that seeks to capture knowledge used during project planning and deliver it for use during project control.     

Brand Image Transfer Through Sponsorship: A Consumer Learning Perspective

Despite the massive growth in sponsorship activity of all kinds, academic research is still in its infancy in this area. This is particularly true with regards the effect of sponsorship on the brand image of the sponsor. This article seeks to address this by producing a conceptual framework of factors that influence sponsorship's effect on brand image transfer (BIT) amongst consumers. The findings from existing research are summarised and highlighted. Where there is a lack of research, 'appropriate' theory from the wider branding literature is used to develop the discussion. Thus, brand knowledge, power, fit and quality are considered as influences on the BIT process. A model of the actual process by which brand image transfers is developed and conditions influencing the strength of the transfer are identified. From this overall analysis, implications for both sponsors and sponsored are discussed and future research directions are outlined.     

Affine multiple yield curve models

We provide a general and tractable framework under which all multiple yield curve modeling approaches based on affine processes, be it short rate, Libor market, or Heath–Jarrow–Morton modeling, can be consolidated. We model a numéraire process and multiplicative spreads between Libor rates and simply compounded overnight indexed swap rates as functions of an underlying affine process. Besides allowing for ordered spreads and an exact fit to the initially observed term structures, this general framework leads to tractable valuation formulas for caplets and swaptions and embeds all existing multicurve affine models. The proposed approach also gives rise to new developments, such as a short rate type model driven by a Wishart process, for which we derive a closed‐form pricing formula for caplets. The empirical performance of two specifications of our framework is illustrated by calibration to market data.     

Issues in fitting theoretical and measurement models in marketing

This article reviews the applications of linear structural equation modeling in business. It further examines the extent to which measurement models are constructed to fit theory models. The consensus appears to be that modelers intuitively use congeneric models without considering the appropriateness of such use. The other measurement models, such as tau equivalent or parallel form models are used very little in the literature. In addition, there is no use of common factor measurement models. The article also examines the extent to which various indices of fit are used in modeling marketing phenomena. Although chi square tests of model fit are used most frequently, the study documents increasing use of yet other indices, which perhaps more accurately reflect the extent to which the model fits.     

A note reconsidering a post-Keynesian model of growth and distribution in the globalization context

We treat an extension of the Metcalfe and Steedman model of growth and distribution in a small open economy with government activity. We show, simultaneously, that certain kinds of taxation and government expenditures will not affect the essential nature of the “Cambridge Equation.” This is important due to the increasing process of Financial Globalization which can be responsible for changing the profit distribution between capitalists and workers. The present note aims at integrating the public sector and the foreign trade together into the model, based on previous literature that, with few exceptions, treats them separately. To do so, a new framework is proposed. Our contribution shows that workers’ income grows when the Current Account in the balance of payments is in surplus, a result not studied by Teixeira and Araújo. The discussion includes recent literature concerning with limits of applicability of such analytical model, dealing with more realistic economies including the process of globalization.     

A study of factors affecting intersection crash frequencies using random-parameter multivariate zero-inflated models

Recent research demonstrates the appropriateness of multivariate regression models in crash count modelling when one specific type of crash counts needs to be analysed, since they can better handle the correlated issues in multiple crash counts. In this paper, a random-parameter multivariate zero-inflated Poisson (RMZIP) regression model is proposed as an alternative multivariate methodology for jointly modelling crash counts simultaneously. Using this RMZIP model, we are able to account for the heterogeneity due to the unobserved roadway geometric design features and traffic characteristics. Our formulation also has the merit of handling excess zeros in correlated crash counts, a phenomenon that is commonly found in practice. The Bayesian method is employed to estimate the model parameters. We use the proposed modelling framework to predict crash frequencies at urban signalized intersections in Tennessee. To investigate the model performances, three models – a fixed-parameter MZIP model, a random-parameter multivariate negative binomial (RMNB) model, and a random-parameter multivariate zero-inflated negative binomial (RMZINB) model – have been employed as the comparison methods. The comparison results show that the proposed RMZIP models provide a satisfied statistical fit with more variables producing statistically significant parameters. In other word, the RMZIP models have the potential to provide a fuller understanding of how the factors affect crash frequencies on specific roadway intersections. A variety of variables are found to significantly influence the crash frequencies by varying magnitudes. These variables result in random parameters and thereby their effects on crash frequencies are found to vary significantly across the sampled intersections.