Change within purchasing and supply management organisations – Assessing the claims from maturity models

It is a wide-held assumption that professional development and change within purchasing and supply management (PSM) organisations can be explained and guided by a maturity model. In this paper the guidance which the maturity model concept offers to understand a PSM organisation's performance is assessed. The methodology is based on the outcomes of a literature review of PSM maturity models, development of an organisational change framework and the learning from three qualitative case studies. An alternative understanding of the development of the PSM organisation is offered through an organisational change framework, composing 1) movement transitions, 2) scalability of change, 3) acceptability of change, and 4) the substantive element of change. The research found that extant PSM maturity models are too rigid for PSM managers to apply, and although maturity models are commonly accepted in PSM literature, in practice, they may produce the opposite effect of what is promised. The PSM maturity models suggest that their application will lead to increased status and influence of PSM within the organisation; expectations that may not be met. PSM organisations’ change processes are subjected to a range of situational and contextual power relations which must be considered in order to advance the specific PSM organisation roles and responsibilities.     

Durations in Panel Data Subject to Attrition: A Note on Estimation in the Case of a Stock Sample1

In the empirical analysis of unemployment durations or job durations, it is generally assumed that the stochastic processes underlying labour market behaviour and the behaviour concerning participation in a panel survey are independent. As a consequence, spells that are incomplete due to attrition can be treated as spells that are subjected to independent right censoring. However, if the assumption of independence is violated, i.e. if for example the probability of dropping out of the panel is related to the rate at which a job is found, then attrition may have to be modelled and estimated jointly with the unemployment duration distribution to avoid biased estimates of the rate at which individuals become employed. A way to model the joint dependence is by means of stochastically related unobserved determinants. We discuss some properties of these kinds of models and state conditions needed to estimate such models in the case of stock sampled duration data.     

Statistical analysis of change in networks

A survey is given of random graphs and random graph processes which can be used to describe and analyze networks that are changing with time. Marko-vian change over time, log-linear models for change, and conditionally uniform models for change are described. It is noted that estimation is usually complex if the random graph involves dependent dyads. Models with deterministic change over time may be a way to avoid the difficulties implied by dependent dyads. Logit regression methods are described that can be used to estimate such models.     

Testing for unit roots in time series models with non-stationary volatility

Many of the key macro-economic and financial variables in developed economies are characterized by permanent volatility shifts. It is known that conventional unit root tests are potentially unreliable in the presence of such behaviour, depending on a particular function (the variance profile) of the underlying volatility process. Somewhat surprisingly then, very little work has been undertaken to develop unit root tests which are robust to the presence of permanent volatility shifts. In this paper we fill this gap in the literature by proposing tests which are valid in the presence of a quite general class of permanent variance changes which includes single and multiple (abrupt and smooth-transition) volatility change processes as special cases. Our solution uses numerical methods to simulate the asymptotic null distribution of the statistics based on a consistent estimate of the variance profile which we also develop. The practitioner is not required to specify a parametric model for volatility. An empirical illustration using producer price inflation series from the Stock–Watson database is reported.     

Predictions of short-term rates and the expectations hypothesis

This paper emphasizes that traditional tests of the EH are based on two assumptions: the expectations hypothesis (EH) per se and an assumption about the expectations generating process (EGP) for the short-term rate. Arguing that conventional tests of the EH need to assume EGPs that may be significantly at odds with the true EGP, we investigate this possibility by analyzing the out-of-sample predictive performances of several models for predicting interest rates, including a few models which assume that the EH holds in its functional form that relates long- to short-term yields. Using US riskless yield data for a 1970–2016 monthly sample and testing methods that take into account the parameter uncertainty, the null hypothesis of an equal predictive accuracy of each model relative to the random walk alternative is hardly ever rejected at intermediate and long horizons. This confirms that, at least at a practical level, the main difficulty with the EH is represented by the effective prediction of short-term rates. We discuss the relevance of these findings for central banks’ use of forward guidance.     

供应链中库存模式的比较分析

通过建立传统库存模式、VMI库存模式和由VMI发展出的一种库存模式的数学模型，分析后两种模式对供应链中生产商成本、零售商成本以及总成本的影响。通过分析发现，后两种模式对各项成本的影响和成本参数有一定的关系。随着参数的变化，它们对同一成本的影响结果也不相同，这为企业的库存模式选择提供了参考依据。     

Attrition in longitudinal panel data and the empirical analysis of dynamic labour market behaviour

In the empirical analysis of unemployment durations and job durations, it is generally assumed that the stochastic processes underlying labour market behaviour and the behaviour concerning participation in a panel survey are independent. However, there are reasons to believe that the probability of dropping out of the panel is related to the rate at which a (different) job is found. If there is such a relation, and if it is ignored, then the estimator of the rate at which individuals become employed or change jobs will generally be inconsistent. In this paper we analyse the relation between the duration spent in a particular labour market state and the duration of panel survey participation, by explicitly modelling and estimating the joint distribution of both durations. The emphasis will be on models allowing for stochastically related unobserved determinants of both types of duration. We estimate models both for unemployment durations and for job durations.     

Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art

Much of the literature on static efficiency measurement models assumes that the inputs are fully used for producing outputs in the same period, with the result that no time interdependence exists between the input utilization and output realizations for a production unit in consecutive periods. A review of the literature on non-parametric dynamic efficiency models identifies five key factors of the inter-temporal dependence between input and output levels over different periods: (i) production delays; (ii) inventories (inventories of exogenous inputs or inventories of intermediate and final products); (iii) capital or generally quasi-fixed factors (and associated embodied technological change, vintage specific capital); (iv) adjustment costs; and (v) incremental improvement and learning models (disembodied technological change). This paper reviews the literature and finds that the dynamic issues associated with adjustment costs and capital have received considerable attention in the literature, whereas the dynamic issues associated with inventories have received less attention. The paper concludes with suggestions for future research such as relaxing the perfect anticipation/knowledge assumption for future variables, prices, and states. Moreover, Dynamic Network Data Envelopment Analysis has provided a unifying framework for some dynamic factors, but further development of these models is necessary including meaningful applications.     

Implementing Change in Public Organizations: The relationship between leadership and affective commitment to change in a public sector context

We propose and test a theoretical framework concerning the relationship between transformational leadership behaviour and affective commitment to change in a public sector context. We apply change management theory to explain how direct supervisors contribute to processes of organizational change, thereby increasing affective commitment to change among employees. While the change leadership literature emphasizes the role of executive managers during change, we conclude that the transformational leadership behaviour of direct supervisors is an important contribution to the successful implementation of change. Furthermore, the results show how the specific context of public organizations determines the transformational leadership behaviour of direct supervisors.     

Weak convergence of tree methods,to price options on defaultable assets

Abstract We discuss a practical method to price and hedge European contingent claims on assets with price processes which follow a jump-diffusion. The method consists of a sequence of trinomial models for the asset price and option price processes which are shown to converge weakly to the corresponding continuous time jump-diffusion processes. The main difference with many existing methods is that our approach ensures that the intermediate discrete time approximations generate models which are themselves complete, just as in the Black-Scholes binomial approximations. This is only possible by dropping the assumption that the approximations of increments of the Wiener and Poisson processes on our trinomial tree are independent, but we show that the dependence between these processes disappears in the weak limit. The approximations thus define an easy and flexible method for pricing and hedging in jump-diffusion models using explicit trees for hedging and pricing. Mathematics Subject Classification (2000): 60B10, 60H35 Journal of Economic Literature Classification: G13     

Retrospective reserves for the insurances of the person in the framework of multistate models

Retrospective reserve is usually meant as the expected accumulated value at a given time of past premimums less benefits. With reference to multistate models, hoth the state of the policy at the time of valuation and its past story must be considered in calculating such expected value. Since it is unlikely that the retrospective reserve can be evaluated for any possible path of the risk, different definitious can be given according to the hypotheses on its story. In this paper we firstly examine the main definitions of retrospective reserve given in the framework of multistate models. Then, we formulate a new definition which generalizes that given in conventional life insurance mathematics. Comparisons among the various definitions are proposed in some examples which, inter alias, show the different behaviour and magnitude of such reserves.     

Sustainable Consumption: Proposal of a Multistage Model to Analyse Consumer Behaviour for Organic Foods

Explanatory models of consumer behaviour can be used to steer decision‐making in the complex task of designing generic strategies to increase sustainable consumption. This paper proposes an operational model which assumes that the purchase of an organic food is a complex process that can be broken down into phases. It is applied to a concrete case – organic olive oil in the Spanish market – quantifying each phase to determine which ones should be acted on to increase demand. Results indicate that it is possible to adopt the model proposed, and that the problems hindering consumption are a lack of confidence in organic certification, not perceiving differences between organic and conventional foods, and the perception of barriers in their purchase. Given the context, marketing communications strategies have a key role to play. This model can be used to analyse the specific situation of each market and propose development strategies. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

The general dynamic factor model: One-sided representation results

Recent dynamic factor models have been almost exclusively developed under the assumption that the common components span a finite-dimensional vector space. However, this finite-dimension assumption rules out very simple factor-loading patterns and is therefore severely restrictive. The general case has been studied, using a frequency domain approach, in Forni et al. (2000). That paper produces an estimator of the common components that is consistent but is based on filters that are two-sided and therefore unsuitable for prediction. The present paper, assuming a rational spectral density for the common components, obtains a one-sided estimator without the finite-dimension assumption.     

Transferability of disaggregate mode choice models

Predictions of aggregate transport mode split for inter-city trips are derived from a disaggregate model of travel demand. A series of tests are performed to assess the limitations of the prediction methodology for disaggregate models, and it is shown that disaggregate models are capable of predictions across diverse travel situations. The disaggregate model predictions are compared with predictions derived from aggregate models such as are currently used in urban transportation planning, and it is shown that disaggregate models based on much smaller data sets predict better than aggregate models while requiring no more information about the predicted population.     

On a double-threshold autoregressive heteroscedastic time series model

Tong's threshold models have been found useful in modelling nonlinearities in the conditional mean of a time series. The threshold model is extended to the so-called double-threshold ARCH(DTARCH) model, which can handle the situation where both the conditional mean and the conditional variance specifications are piecewise linear given previous information. Potential applications of such models include financial data with different (asymmetric) behaviour in a rising versus a falling market and business cycle modelling. Model identification, estimation and diagnostic checking techniques are developed. Maximum likelihood estimation can be achieved via an easy-to-use iteratively weighted least squares algorithm. Portmanteau-type statistics are also derived for checking model adequacy. An illustrative example demonstrates that asymmetric behaviour in the mean and the variance could be present in financial series and that the DTARCH model is capable of capturing these phenomena.     

Identification and information in monotone binary models

This paper considers binary response models where errors are uncorrelated with a set of instrumental variables and are independent of a continuous regressor v$v$, conditional on all other variables. It is shown that these exclusion restrictions are not sufficient for identification and that additional identifying assumptions are needed. Such an assumption, introduced by Lewbel [Semiparametric qualitative response model estimation with unknown heteroskedasticity or instrumental variables. Journal of Econometrics 97, 145–177], is that the support of the continuous regressor is large, but we show that it significantly restricts the class of binary phenomena which can be analysed. We propose an alternative additional assumption under which β$\beta$ remains just identified and the estimation unchanged. This alternative assumption does not impose specific restrictions on the data, which broadens the scope of the estimation method in empirical work. The semiparametric efficiency bound of the model is also established and an existing estimator is shown to achieve that bound. The efficient estimator uses a plug-in density estimate. It is shown that plugging in the true density rather than an estimate is inefficient. Extensions to ordered choice models are provided.     

Inertia in the attributional content of annual accounting narratives

Narrative disclosures in annual reports reflect explanatory activities in which specific attribution patterns can be identified. Research on corporate attributional behaviour within the context of financial accounting narratives has documented this behaviour and evidenced significant preferences for certain kinds of explanations in particular circumstances. This kind of research typically relies on cross-sectional data. There exist few statistically validated conclusions regarding the character and consequences of such verbal behaviour over time. This paper reports on a study investigating the change in narrative explanation practices over time. In this longitudinal research special attention is given to the relative strength of consistency and inertial forces on the attributional behaviour in annual reports. It is argued that there are a variety of forces that make that the explanatory patterns in annual reports are likely to be very similar year after year. Reporting practices can be to a great extent unadaptive, in the sense that they become programmed through the development of habit, precedents, traditions and formalized procedures. This is not to say that reporting practices do not change, but that changes even in the way corporate outcomes and actions are explained, are expected to be modest. The purpose of the research was to determine the extent to which the attributional content and framing in annual narrative reports changed over a period of eight years, and whether these changes were related to certain organizational characteristics of the reporting companies conceptualized as potential sources of inertial forces. Overall the results confirm a significant degree of consistency in the attributional content of accounting narratives over time. Evidence of an inertial effect of company listing status and performance history was convincingly present as to the assertiveness aspects of attributional behaviour and as to the differential use of accounting language in the explanation of financial accounting outcomes.     

An insight into the specification of the input-output set for DEA-based bank efficiency measurement

Data envelopment analysis (DEA) has become one of the most widely used instruments for measuring bank efficiency. However, its application encounters many problems, which is evidenced by continuous evolvements in the DEA method so far. Our paper addresses the pitfalls of DEA in the context of measuring bank efficiency, with focus on the specification of performance factors. We aim at examining whether the input-output specification for banks in DEA applications is in consistence with the criteria upon which banks make decisions. Four bank behaviour models which are most popularly employed to determine input and output factors in DEA studies—the intermediation approach, production approach, user cost approach and value added approach—are comprehensively discussed and reviewed. The comparative reflection on the bank behaviour models and the standard DEA models shows that the input-output related pitfalls of a DEA application are associated with its implicitly fixed preference structure, flexible weight determination and limited explanatory power. Due to the pitfalls, the conventional DEA models may fail to capture bank behaviours. In such cases, DEA results can hardly reflect the performance in its true sense, i.e. how banks perform against the goals that they decide to pursue. The findings suggest focusing on (DEA-based) performance measurement from a goal-oriented perspective, i.e. from the point of view of multi criteria decision making.