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A large number of studies indicate that coercive forms of organizational control and performance management in health care services often backfire and initiate dysfunctional consequences. The purpose of this article is to discuss new approaches to performance management in health care services when the purpose is to support innovative changes in the delivery of services.

The article represents cross-boundary work as the theoretical and empirical material used to discuss and reconsider performance management comes from several relevant research disciplines, including systematic reviews of audit and feedback interventions in health care and extant theories of human motivation and organizational control.

An enabling approach to performance management in health care services can potentially contribute to innovative changes. Key design elements to operationalize such an approach are a formative and learning-oriented use of performance measures, an appeal to self- and social-approval mechanisms when providing feedback and support for local goals and action plans that fit specific conditions and challenges.

The article suggests how to operationalize an enabling approach to performance management in health care services. The framework is consistent with new governance and managerial approaches emerging in public sector organizations more generally, supporting a higher degree of professional autonomy and the use of nonfinancial incentives.

This study aims to enhance storage and distribution operations at a pharmaceutical supply center (PSC) in primary health care (PH) using lean health care (LH) tools. Supply centers for health products, medications and supplies have unique characteristics compared to centers for other goods due to complex processes, specific services, diverse stakeholders and multiple interactions. The authors adapt LH tools to address these complexities and meet industry-specific needs.

The investigation unit is a PSC in a large southern Brazilian city, and the processes analyzed are the storage and distribution of medications. The authors performed action research from June 2019 to February 2020. Data collection and problem diagnosis involved the development of a value stream mapping.

The authors adapted the overall equipment effectiveness calculation, efficiency analysis, and loss classification for PSC operations. Eighteen core issues were found: waiting, movement, transport, stock, inadequate processing, defects and human potential losses. The authors proposed waste reduction tools and practices. Inadequate storage conditions may compromise medicine quality, efficacy and safety. This can result from lacking physical structures or noncompliance with procedures. Next, the authors recommend simulating scenarios for validation before implementation.

The study explored ways to enhance layout and medicine distribution at the PSC, focusing on reducing loss and cost impact.

Originality lies in LH application in a PSC of PH, often applied in secondary or tertiary health levels like hospitals. The novelty necessitated adaptations of tools for future PSC applications.

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

How do radical technological fields become naturalized and taken for granted? This is a fundamental question given both the positive and negative hype surrounding the emergence of many new technologies. In this chapter, we study the emergence of the US nanotechnology field, focusing on uncovering the mechanisms by which leaders of the National Nanotechnology Initiative managed hype and its concomitant legitimacy challenges which threatened the commercial viability of nanotechnology. Drawing on the cultural entrepreneurship literature at the interface of strategy and organization theory, we argue that the construction of a naturalizing frame – a frame that focuses attention and practice on mundane, “rationalized” activity – is key to legitimating a novel and uncertain technological field. Leveraging the insights from our case study, we further develop a staged process model of how a naturalizing frame may be constructed, thereby paving the way for a decrease in hype and the institutionalization of new technologies.

Despite being a flexible tool that can address several macroeconomic issues, Dynamic Stochastic General Equilibrium (DSGE) models have been rarely used to analyse the interaction between monetary and fiscal policy until the post-financial crisis, leaving a gap in the analysis of how government consumption affects the transmission mechanism of monetary policy. This motivates this paper to analyse how government consumption affects the dynamics of a small open economy, once the former is included in a non-separable form to the utility function. To the best of the authors' knowledge, this issue has not been addressed by the literature, and the authors aim to do so in this paper.

A standard New Keynesian model for a small open economy is used to allow for the presence of non-separable government consumption in the utility function. The model is supported by panel regressions.

The inclusion of Government consumption dampens the transmission mechanism of monetary policy. The degree of openness dampens the crowding out effect of fiscal policy to monetary policy, as the exchange rate channel empowers it. Empirical estimates for 35 OECD countries support the theoretical findings of the model.

The effect of government consumption on the transmission mechanism of MP has not been addressed in the literature. This paper contributes to the literature by addressing this issue.

• • The inclusion of Government consumption dampens the transmission mechanism of monetary policy.

• • The degree of openness alleviates the crowding out effect of fiscal policy to monetary policy, as the exchange rate channel empowers it.

• • Empirical estimates for 35 OECD countries support the theoretical findings of the model.

• The inclusion of Government consumption dampens the transmission mechanism of monetary policy.

• The degree of openness alleviates the crowding out effect of fiscal policy to monetary policy, as the exchange rate channel empowers it.

• Empirical estimates for 35 OECD countries support the theoretical findings of the model.

The principal aim of this paper is to review three basic theoretical growth models, namely the Harrod-Domar model, the Solow model and the Ramsey model, and examine their implications for economic policies.

The paper utilizes a positivist research framework that emphasizes the causal relationships between the variables in each of the three models. Mathematical methods are employed to formulate and examine the three models under study. Since the paper is theoretical, it does not use any empirical data although numerical illustrations are provided whenever they are appropriate.

The Harrod-Domar model explains why countries with high rates of saving may also enjoy high rate of economic growth. Both the Solow and Ramsey models can be used to explain the medium-income trap. The paper examines the impact of Covid shocks on the macroeconomy. While the growth rate can be recovered, it may not always possible to recover the output level.

For the Harrod-Domar model, the public spending decreases the private consumption at the period 1, but there is no change in the capital stock and hence the production in subsequent periods. For the Ramsey model with AK production function, both the private consumption and the outputs will be lowered. In both the Harrod-Domar and Ramsey models with Cobb-Douglas production function, if the debt is not high and the interest rate is sufficiently low, it is better to use public debt for production rather than for consumption. If the country borrows to recover the Total Factor Productivity after the Covid pandemic, both the Harrod-Domar and Ramsey models with Cobb-Douglas production function show that the rate of growth is higher for the year just after the pandemic but is the same as before the pandemic.

The economy can recover the growth rate after a Covid shock, but the recovery process will generally take many periods.

This paper focuses on economic implications and does not aim to examine social implications of policy changes or Covid-type shock.

The paper provides a comparison of three basic growth models with respect to public spending, public debts and repayments and Covid-type shocks.

By examining the impact of product innovation on abnormal financial returns following the launch of new products, this study aims to test the explanatory power of a new compound measure of product innovativeness (Ganbaatar and Douglas, 2019).

It is a longitudinal study in which the authors used the compound product innovativeness score (CPIS) for the first time to measure product innovativeness. The abnormal financial returns are estimated through the event study design, where four different models are used. Artificial neural network analysis is done to determine the impact of the CPIS on abnormal returns by utilising a hexic polynomial regression model.

The authors find effect sizes that substantially exceed practically significant levels and that the CPIS explain 65% of the variance in the firm’s abnormal returns in market valuation. Moreover, new-to-the-market novelty predicts 83% of the variation, while new-to-the-firm (catch-up) innovation insignificantly impacts firm value.

This paper demonstrates how the CPIS, an objective and direct measure of product innovativeness, can be used to gain more insight into the innovation effect.

Implications for the business practice of this study include the necessity of relentless innovation by firms in contested differentiated markets, particularly where technological advance is ongoing. Larger and mature firms must practice corporate entrepreneurship to renew their products on a continuous basis to avoid slipping backwards in their markets. Innovation leadership, rather than following the leader, is also important to increase competitive advantage, given the result that innovation followship does not produce abnormal financial returns.

In this study, the authors focused on the effect of product innovativeness on firm performance. While the literature affirms a positive relationship between innovation and firm performance, the effect size of this relationship varies, due largely to the authors contend to simplistic measures of innovativeness. In this study, the authors adopt the relatively novel “compound” measure of product innovativeness (Ganbaatar and Douglas, 2019) to better encapsulate the nuances of both technical novelty and market novelty. This measure of product innovativeness is applicable to firms of all sizes but is more easily applied to entrepreneurial new ventures and SMEs, and it avoids the shortcomings of prior firm-level and subjective measures of innovativeness for both smaller and larger firms. Using a more effective analytical method (Artificial Neural Network), the authors investigated whether there is a “practically” significant effect size due to product innovation, which could be valuable for entrepreneurs in practice. The authors show that the CPIS measure can very effectively explain abnormalities in the stock market, exhibiting a moderate effect size and explaining 65% of the variation in abnormal returns.

This study aims to propose and numerically assess different ways of discretising a very weak formulation of the Poisson problem.

We use integration by parts twice to shift smoothness requirements to the test functions, thereby allowing low-regularity data and solutions.

Various conforming discretisations are presented and tested, with numerical results indicating good accuracy and stability in different types of problems.

This is one of the first articles to propose and test concrete discretisations for very weak variational formulations in primal form. The numerical results, which include a problem based on real MRI data, indicate the potential of very weak finite element methods for tackling problems with low regularity.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

This chapter contributes to the Public Value (PV) literature in relation to accounting by providing evidence on its content's operationalization through performance measurement. In particular, it establishes the link with Sustainable Development Goals (SDGs), which may work as guiding principles of a public organization’s action. Accordingly, organizations embedding SDGs include them in their strategic decisions and disclose them through performance measurement and narratives.

The SDGs' presence is explored in the PV of a sample of Italian health institutes through documentary analysis of their performance plans. The aim is to verify if and how SDGs are pursued and whether the COVID-19 pandemic has affected PV content.

Besides Goal No. 3 (Health), the PV content of the investigated institutes contains various SDGs. Before the pandemic, their PV was aligned with SDGs mainly related to prosperity, economic growth and social inclusion. In the following period, the number of SDGs increased, introducing planet and environmental protection dimensions. No one explicitly mentions pursuing SDGs, revealing a non-institutionalized sensitivity of managers towards SDGs. The analysis distinguishes between ‘core’ SDGs, revealed mostly by traditional performance measures disclosing the achievement of institutes' mission, and ‘complementary’ SDGs, expressed mostly through narratives. This can derive from performance measurement, which employs the language of performativity, while the contribution to society is relegated in the narratives, making them less incisive.