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This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/01443579810192772. When citing the article, please cite: Gregory N. Stock, Noel P. Greis, John D. Kasarda, (1998), “Logistics, strategy and structure: A conceptual framework”, International Journal of Operations & Production Management, Vol. 18 Iss: 1, pp. 37 - 52.

The purpose of this paper is to examine the relationship between patient safety culture and hospital performance using objective performance measures and secondary data on patient safety culture.

Patient safety culture is measured using data from the Agency for Healthcare Research and Quality’s Hospital Survey on Patient Safety Culture. Hospital performance is measured using objective patient safety and operational performance metrics collected by the Centers for Medicare and Medicaid Services (CMS). Control variables were obtained from the CMS Provider of Service database. The merged data included 154 US hospitals, with an average of 848 respondents per hospital providing culture data. Hierarchical linear regression analysis is used to test the proposed relationships.

The findings indicate that patient safety culture is positively associated with patient safety, process quality and patient satisfaction.

Hospital managers should focus on building a stronger patient safety culture due to its positive relationship with hospital performance.

This is the first study to test these relationships using several objective performance measures and a comprehensive patient safety culture data set that includes a substantial number of respondents per hospital. The study contributes to the literature by explicitly mapping high-reliability organization (HRO) theory to patient safety culture, thereby illustrating how HRO theory can be applied to safety culture in the hospital operations context.

This paper empirically examines the process of acquiring technology from a source, external to the firm, and incorporating it into a new product or operational process under development. We refer to this key activity in product and process innovation as external technology integration. This paper develops a conceptual model of external technology integration based on organizational information processing theory and a wide range of technology management literature. Field interviews were conducted to evaluate the validity of the model across diverse settings. Our results indicate general support for the conceptual model. We close with a discussion of the implications of this study for both theory and practice.

The purpose of this study is to explore the use of patient safety initiatives (PSIs) at the US hospitals. These PSIs include such approaches as open discussion of errors, education and training, and system redesign. In particular, the paper seeks to examine factors that influence the implementation of PSIs as well as the benefits realized from their implementation.

The paper draws on the TQM and medical safety literatures to develop a conceptual framework for improving patient safety. Extensive survey data were gathered from 252 hospitals throughout the US to test McFadden et al.'s model of the factors influencing successful implementation of PSIs.

Certain barriers (lack of top management support, lack of resources, lack of incentives and lack of knowledge) significantly impeded implementation while other factors (perceived importance of PSIs) facilitated implementation. It was also found that implementation of PSIs was associated with benefits to the hospital in areas such as medical error reduction, cost reduction, and patient satisfaction.

The use of a single respondent represents a possible limitation. Future research will explore organizational culture and its relationship to patient safety.

The findings provide direction for implementing more effective PSIs at hospitals.

The paper contributes to the literature on patient safety and medical errors by testing specific mechanisms that are associated with successful implementation of PSIs.

The purpose of this paper is to examine empirically how operational performance and contextual factors contribute to differences in overall patient care costs across different hospitals.

Administrative data are employed from a sample of hospitals in New York State to construct measures of contextual factors, operational performance, and cost per patient. Operational performance and cost variables are adjusted to account for case mix differences across hospitals. Hierarchical regression is used to analyze the effects of contextual and operational variables on cost performance.

Increased length of stay, increased patient volume, and educational mission were associated with higher cost per patient. Mortality performance was associated with lower cost per patient. However, it was not found that location, size, or ownership status had a significant relationship with cost performance.

This paper identifies several significant relationships between contextual and operational variables and hospital costs. From a managerial perspective, these findings highlight the fact that some drivers of cost in hospitals are under the control of managers. One of the primary cost drivers in the study is length of stay, which implies that there is significant room for improvement in healthcare performance through a focus on operational excellence.

For researchers, the present study highlights the relative importance of operational versus contextual factors, with respect to cost performance in hospitals. The results of this study also provide direction for additional research into the role operational performance might play in determining the overall organizational performance in a hospital.

Presents a framework for explaining the relationship between strategy, structure, and logistics in the context of a changing environment. In response to new competitive pressures, a manufacturing enterprise is emerging in which resources may now be dispersed worldwide. As distances between production facilities and pressures for fast delivery increase, the coordination of these dispersed manufacturing resources becomes a critical activity. Argues that logistics is well‐positioned to assume a unique role in bridging strategy and structure in the new manufacturing environment. Develops a new model of the strategy‐structure relationship that recognizes the integral role that logistics will play in creating the “fit” necessary to achieve competitive success. The framework suggests that performance will be higher when the firm’s strategy and structure are consistent with the strengths inherent in the firm’s logistics choices.

As hospital costs continue to rise, increasing attention is being paid to the way these organizations are and should be managed. This attention typically comes in the form of focus on costs of services, quality (often measured through mortality rates) and length of stay. Hospital management has a broad array of choices at their disposal to address these challenges. As service operations, hospitals present a significant opportunity to apply the many tools and techniques from the field of operations strategy to this important industry. The objective of this paper is to use the operations strategy framework to assess the relationship between a set of operational elements and hospital performance in terms of average length of stay (ALOS), so that hospital managers improve the effectiveness and efficiency of patient care of their hospitals.

Using the structural and infrastructural operations strategy framework, this study examines the relationship between several strategic variables and hospital performance. To analyze these relationships the paper employs data from the population of hospitals in New York State. The performance measure is the ALOS for patients, adjusted for the mix and severity of cases in each hospital.

The paper finds that a direct relationship exists between the dependent variable and location, capacity, and teaching status, and failed to find a direct relationship for capital expenditures, salary, and staffing levels. However, the paper did find significant interaction effects between capital expenses and both salary and staffing levels.

There appear to be trade‐offs between capital expenditures and workforce decisions that have significant implications in light of current and expected hospital staffing shortages. The findings indicate that reductions in staff may not be perfectly replaced by corresponding increases in capital expenditures.

This paper further expands the body of research that addresses the important challenges hospitals face from an operations management perspective.

In this paper, it is argued that previous estimates of the expected cost of equity and the expected arithmetic risk premium in the UK show a degree of upward bias. Given the importance of the risk premium in regulatory cost of capital in the UK, this has important policy implications. There are three reasons why previous estimates could be upward biased. The first two arise from the comparison of estimates of the realised returns on government bond (‘gilt’) with those of the realised and expected returns on equities. These estimates are frequently used to infer a risk premium relative to either the current yield on index‐linked gilts or an ‘adjusted’ current yield measure. This is incorrect on two counts; first, inconsistent estimates of the risk‐free rate are implied on the right hand side of the capital asset pricing model; second, they compare the realised returns from a bond that carried inflation risk with the realised and expected returns from equities that may be expected to have at least some protection from inflation risk. The third, and most important, source of bias arises from uplifts to expected returns. If markets exhibit ‘excess volatility’, or f part of the historical return arises because of revisions to expected future cash flows, then estimates of variance derived from the historical returns or the price growth must be used with great care when uplifting average expected returns to derive simple discount rates. Adjusting expected returns for the effect of such biases leads to lower expected cost of equity and risk premia than those that are typically quoted.

After the collapse of communist and socialist regimes at the beginning of 1990s, a number of Central and Eastern European (CEE) economies started their journey into capitalism by establishing private property and capital markets. As a result, a number of stock markets have since been established in the region. Since then, they have displayed considerable growth in size and degree of sophistication, and they have attracted the interest of academics for a number of reasons. First, these markets provide a possibility to re-examine existing asset-pricing models and pricing anomalies in the conditions of the evolving markets. Market efficiency of the CEE markets is tested in Ratkovicova (1999) and Gilmore and McManus (2001); a version of the CAPM is tested in Charemza and Majerowska (2000); Mateus (2004) explores the predictability of European emerging market returns within an unconditional asset-pricing framework while the January-pricing anomaly is studied in Henke (2003). Second, in the light of growing interdependencies between world equity markets due to enhanced capital movements, numerous studies have investigated the extent to which emerging European stock markets are integrated with global markets, and the extent to which they are subjects to global shocks (Gelos & Sahay, 2000; Gilmore & McManus, 2002; Scheicher, 2001). Among the CEE markets, those of the Vysegrad countries (Poland, Hungary and the Czech Republic) have attracted most of the attention of the academics due to their economies faster growth relative to their regional counterparts (Slovakia, Slovenia, Bulgaria, Croatia and Baltic countries), in addition to political stability and their (successfully realized) prospects of joining the European Union (EU).