Information technology and performance management for build‐to‐order supply chains

Value Implications of Sourcing Electronic Health Records: The Role of Physician Practice Integration

Should hospitals source electronic health records (EHR) systems from a single vendor or multiple vendors to deliver high-value care? We study hospitals’ EHR sourcing strategies based on their degree of integration with physician practices and its impact on the value of healthcare delivered. We propose a novel framework to define healthcare value as the extent to which a hospital effectively expends clinical resources to deliver services that improve patient outcomes. Drawing on modular systems and transaction cost economics theories, we propose a moderated-mediation model that explores the pathways through which EHR sourcing strategies can create value in healthcare. We test our research hypotheses on a large, longitudinal sample of U.S. hospitals and observe that hospitals with EHR configurations closer to single sourcing strategies exhibit greater health information sharing compared with hospitals with multisourced EHR systems. Furthermore, we find that hospital-physician practice integration moderates the impact of single sourcing on health information sharing, which in turn, improves value. Specifically, tighter integration between hospitals and physician practices can create greater value if it is aligned with hospitals’ EHR sourcing strategies. As the healthcare industry moves toward value-based payment reform, our findings provide a useful roadmap to practitioners and policy makers to improve the performance of hospitals and healthcare providers.

History: Rajiv Kohli, Senior Editor; Sunil Wattal, Associate Editor.

Funding: I.R. Bardhan thanks the Foster Parker Centennial Professorship and the Dean’s Research Excellence Grant at the McCombs School of Business at UT Austin for generous financial support. C. Bao thanks the Spears Fellowship at Oklahoma State University for financial support.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1183 .

Exploring the influence of big data on city transport operations: a Markovian approach

Purpose

The purpose of this paper is to advance knowledge of the transformative potential of big data on city-based transport models. The central question guiding this paper is: how could big data transform smart city transport operations? In answering this question the authors present initial results from a Markov study. However the authors also suggest caution in the transformation potential of big data and highlight the risks of city and organizational adoption. A theoretical framework is presented together with an associated scenario which guides the development of a Markov model.

Design/methodology/approach

A model with several scenarios is developed to explore a theoretical framework focussed on matching the transport demands (of people and freight mobility) with city transport service provision using big data. This model was designed to illustrate how sharing transport load (and capacity) in a smart city can improve efficiencies in meeting demand for city services.

Findings

This modelling study is an initial preliminary stage of the investigation in how big data could be used to redefine and enable new operational models. The study provides new understanding about load sharing and optimization in a smart city context. Basically the authors demonstrate how big data could be used to improve transport efficiency and lower externalities in a smart city. Further how improvement could take place by having a car free city environment, autonomous vehicles and shared resource capacity among providers.

Research limitations/implications

The research relied on a Markov model and the numerical solution of its steady state probabilities vector to illustrate the transformation of transport operations management (OM) in the future city context. More in depth analysis and more discrete modelling are clearly needed to assist in the implementation of big data initiatives and facilitate new innovations in OM. The work complements and extends that of Setia and Patel (2013), who theoretically link together information system design to operation absorptive capacity capabilities.

Practical implications

The study implies that transport operations would actually need to be re-organized so as to deal with lowering CO2 footprint. The logistic aspects could be seen as a move from individual firms optimizing their own transportation supply to a shared collaborative load and resourced system. Such ideas are radical changes driven by, or leading to more decentralized rather than having centralized transport solutions (Caplice, 2013).

Social implications

The growth of cities and urban areas in the twenty-first century has put more pressure on resources and conditions of urban life. This paper is an initial first step in building theory, knowledge and critical understanding of the social implications being posed by the growth in cities and the role that big data and smart cities could play in developing a resilient and sustainable transport city system.

Originality/value

Despite the importance of OM to big data implementation, for both practitioners and researchers, we have yet to see a systematic analysis of its implementation and its absorptive capacity contribution to building capabilities, at either city system or organizational levels. As such the Markov model makes a preliminary contribution to the literature integrating big data capabilities with OM capabilities and the resulting improvements in system absorptive capacity.

Performance measurement and metrics in supply chains: an exploratory study

Purpose

– The purpose of this paper is to explore the approaches and metrics used to measure supply chain (SC) performance, and to understand the relative perceived importance of such measures.

Design/methodology/approach

– This research is based on empirical data captured through a survey of SC professionals in a variety of business sectors.

Findings

– The research confirms the importance of the balanced scorecard (BSC) approach, with BSC, SCOR and economic value added being the most commonly used tools. Economic metrics dominate, focused on cost and customer service. While social and environmental-related measures are of emerging importance, they appear to be of similar importance to economic metrics only when backed up by a legal obligation.

Research limitations/implications

– The small sample of 51 companies was based on access and the group is not wholly representative of all businesses. Respondents were mainly managers from EU countries involved in procurement, logistics and transport activities. Surveyed companies included manufacturing, automotive, retail, logistics services and wholesaling businesses.

Practical implications

– The common key performance indicators (KPI’s) are identified. These include measures related to: quality, efficiency, responsiveness, health and safety, employees, emission, natural resources utilisation, waste and recycling. Issues that influence the usage of measurement systems as well as the company and SC levels are ranked.

Social implications

– Implementation of a monitoring system and subsequent usage of the collected data may help to reduce negative external impacts on society and the environment.

Originality/value

– The field of SC performance management is still developing, with growing empirical work. Nevertheless this paper is one of the first attempts to carry out such an analysis focused on metrics and their usage. The survey instrument has been tested and can now be applied to other contexts.