Using Partial Least Squares in Operations Management Research: A Practical Guideline and Summary of Past Research

The partial least squares (PLS) approach to structural equation modeling (SEM) has been widely adopted in business research fields such as information systems, consumer behavior, and marketing. The use of PLS in the field of operations management is also growing. However, questions still exist among some operations management researchers regarding whether and how PLS should be used. To address these questions, our study provides a practical guideline for using PLS and uses examples from the operations management literature to demonstrate how the specific points in this guideline can be applied. In addition, our study reviews and summarizes the use of PLS in the recent operations management literature according to our guideline. The main contribution of this study is to present a practical guideline for evaluating and using PLS that is tailored to the operations management field. (C) 2012 Elsevier B.V. All rights reserved

Antecedents and Consequences of New Product Development Practices and Software Tools: An Exploratory Study

Many development practices and software tools enable new product development (NPD), yet few empirical studies shed light on the project characteristics and project contexts driving their use. Using a cross-sectional sample of NPD projects, this study examines how project characteristics and availability of information technology (IT) infrastructure relate to the use of NPD practices and software tools. We also examine how the extent of their use is associated with NPD project performance. The results indicate that different project characteristics influence the use of NPD practices and software tools, with project complexity associated with software tool use, but project uncertainty associated with NPD practice use. Also, customer facing IT infrastructure is associated with the use of NPD practices, while manufacturing plant IT infrastructure is associated with the use of design/validation software tools. Moreover, use of NPD practices has a positive association with all project-level performance metrics examined in this study, and as a result, a greater impact on overall market success. In comparison, the performance impacts of software tools appear relatively limited, with only design/validation software tools exhibiting a strong positive association with product performance quality and a weak positive association with time-to-market and responsiveness. Communication/teamwork software tools exhibit no such impact

Collaborative Product Development: The Effect of Project Complexity on the Use of Information Technology Tools and New Product Development Practices

Collaboration is an essential element of new product development (NPD). This research examines the associations between four types of information technology (IT) tools and NPD collaboration. The relationships between NPD practices and NPD collaboration are also examined. Drawing on organizational information processing theory, we propose that the relationships between IT tools and NPD collaboration will be moderated differently by three project complexity dimensions, namely, product size, project novelty, and task interdependence, due to the differing nature of information processing necessitated by each project complexity dimension. Likewise, the moderation effects of the project complexity dimensions on the relationship between NPD practices and NPD collaboration will also be different. We test our hypotheses using data from a sample of NPD projects in three manufacturing industries. We find that IT tools are associated with collaboration to a greater extent when product size is relatively large. In contrast, IT tools exhibit a smaller association with collaboration when project novelty or task interdependence is relatively high. NPD practices are found to be more significantly associated with NPD collaboration under the contingency of high project novelty or high task interdependence. The findings provide insights about circumstances where several popular IT tools are more likely to facilitate collaboration, thus informing an NPD team’s IT adoption and use decisions

Impacts of information technology on mass customization capability of manufacturing plants

Purpose: The impact of information technology (IT) on mass customization (MC) capability has been implied in the literature but seldom subjected to empirical examination. This study seeks to theoretically relate four types of IT applications with MC capability and empirically examines these relationships. Design/methodology/approach: This study identifies four types of IT that potentially support MC capability, including product configurator IT, new product development IT, manufacturing IT, and supplier collaboration IT. Drawing on organizational information processing theory, this study associates the four IT types with a manufacturer\u27s MC capability. A structural equation model is tested using survey data collected from a sample of manufacturing plants that focus on product customization. Findings: The empirical results indicate that two of the four IT types strongly support a manufacturer\u27s MC capability. Research limitations/implications: No strong relationship between configurator IT and MC was observed, which calls for further investigation. Data used are cross-sectional in nature. A set of refined IT measures should be developed in future studies. In addition, future studies could control for the effects of more variables that may impact IT use by mass customizers. Practical implications: The paper identifies managerial opportunities for investing in IT to support or enhance MC capability. Originality/value: This study provides a theoretical foundation for the IT-MC relationship and develops a classification framework of IT applications in manufacturing plants. The study is one of the first efforts that empirically examines the impact of multiple types of IT applications on MC. © Emerald Group Publishing Limited

A Perspective on Sustainable Computational Chemistry Software Development and Integration

The power of quantum chemistry to predict the ground and excited state properties of complex chemical systems has driven the development of computational quantum chemistry software, integrating advances in theory, applied mathematics, and computer science. The emergence of new computational paradigms associated with exascale technologies also poses significant challenges that require a flexible forward strategy to take full advantage of existing and forthcoming computational resources. In this context, the sustainability and interoperability of computational chemistry software development are among the most pressing issues. In this perspective, we discuss software infrastructure needs and investments with an eye to fully utilize exascale resources and provide unique computational tools for next-generation science problems and scientific discoveries