Statistical Power in Operations Management Research

This paper discusses the need and importance of statistical power analysis in field-based empirical research in Production and Operations Management (POM) and related disciplines. The concept of statistical power analysis is explained in detail and its relevance in designing and conducting empirical experiments is discussed. Statistical power reflects the degree to which differences in sample data in a statistical test can be detected. A high power is required to reduce the probability of failing to detect an effect when it is present. This paper also examines the relationship between statistical power, significance level, sample size and effect size. A probability tree analysis further explains the importance of statistical power by showing the relationship between Type 11 errors and the probability of making wrong decisions in statistical analysis. A power analysis of 28 articles (524 statistical tests) in the Journal of Operations Management and in Decision Sciences shows that 60% of empirical studies do not have high power levels. This means that several of these tests will have a low degree of repeatability. This and other similar issues involving statistical power will become increasingly important as empirical studies in POM study relatively smaller effects

A Market-Utility Approach to Scheduling Employees

[Excerpt] Scheduling front-line service providers is a constant challenge for hospitality managers, given the inevitable tradeoff between service standards and operating expense. Traditional employee scheduling typically applies a cost-minimization approach to specify the level of front-line service providers who will be available to meet periodic demand. That cost includes the opportunity cost of lost customers, which is part of the pseudo-costs of understaffing. A confounding and often ignored effect, however, is the benefit generated by maintaining high service levels in a system where capacity exceeds demand. That is, scheduling more frontline service providers than the minimum level necessary to provide acceptable customer service (what might be considered to be overstaffing in some rubrics) may mean that customers receive service that is better than they expected (or what company standards prescribe). In this paper we report on a scheduling approach that explicitly considers the interrelationships among customer preferences, customer demand, waiting times, and scheduling decisions. This approach, which we call the market-utility model for scheduling (MUMS), helps managers consider the dynamics of scheduling service employees. First, we discuss the components that make up this approach, which includes methods from customer-preferences modeling, service-capacity planning, and the four tasks of labor scheduling proposed by Thompson. Next, we\u27ll show how the model applies to balancing queue lengths and operating costs for an airport food-court vendor. Finally, we discuss the value of MUMS for hospitality managers

Thermodynamic Analysis of Phenylpropanoid Pathway in Arabidopsis Thanliana

Biofuels represent a renewable alternative to traditional fossil fuels. As dependence on fossil fuels rise so does the importance of improving the production of alternative fuels. Lignin poses one obstacle in the development of such alternative fuels. Its presence strengthens cell walls and hinders degradation of polysaccharides into monosaccharides, increasing cost and time while decreasing efficiency of the process. Lignin is composed of three monolignols, each of which is produced through the Phenylpropanoid pathway; a series of chemical reactions. This work aims to determine which reactions in the pathway are least thermodynamically favorable and thus most limiting. From metabolic mapping techniques on the Phenylpropanoid pathway in Arabidopsis Thanliana and thermodynamic data on the Gibbs free energy of formation for the biochemical compounds, the change in Gibbs free energy of the reaction at intracellular conditions is calculated. For compounds which data is unavailable, Group Contribution methods are used to determine the Gibbs free energy of formation. Reactions involving Cinnamoyl-CoA reductase, shikimate O-hydroxycinnamoyltransferase, and 4-coumarate-CoA ligase yielded positive Gibbs free energy values in the pathway. Since reactions involving these enzymes have positive Gibbs free energy values, these reactions require the greatest concentration of enzyme in order to facilitate production of the three monolignols. Knocking out these enzymes should result in a decrease in monolignol and lignin production

Service Capacity Design With an Integrated Market Utility-Based Method

[Excerpt] The purpose of this chapter is to present a model that integrates customer preferences and service design. In response to the need for interdisciplinary service management research, we present a framework that specifies the key elements of an integrated market utility-based model (MUM) and a method for determining optimal service designs based on customer needs and preferences. We also explore the relationships among revenue, capacity costs, and those service design attributes that have significant operational consequences. Our model builds on the topics we have described and integrates customer utility models that are commonly used in market research with capacity variables and their corresponding costs that are typical operations management issues. The proposed method is general and can be adapted for different types of service operations

Designing and Positioning Food Services for Multicultural Markets

[Excerpt] Businesses that seek to develop an appropriate operations strategy for serving a multicultural customer market face challenges that are distinct from businesses that serve a relatively homogeneous local market. While the strategic implications of expanding services from a domestic market to international locations have been well documented, the issue of dealing with multinational customers at a single location has largely been neglected by researchers, as far as we can determine. This paper attempts to fill the research gap by presenting a method for determining the extent to which restaurant managers should maintain standard menus and food items, as opposed to customizing their operations for different ethnic and cultural groups. To that end, we applied a customer-based approach to help managers at four international-airport food outlets to improve their food- service revenues from their three major passenger groups: English-, Japanese-, and Spanish-speaking customers. In this case, language preference was used as a proxy for cultural identity. We submit that although there are many differences among, say, English-speaking peoples, they are more similar to each other than they are to, say, Spanish speakers. Moreover, the language a person speaks is a substantial factor in trying to communicate in a particular location. One can guess that Japanese speakers in the United States, for example, might experience more language barriers than either English or Spanish speakers. We present an approach for modeling the preferences of different cultural groups, evaluating the differences among the groups, and determining a strategy to maximize market share for each of the four food-service providers that we studied. Indeed, one food-service vendor implemented our study\u27s recommendations and enjoyed a substantial revenue gain over the previous year\u27s same-period sales. We believe that the method we propose has valuable implications for any service provider who must consider operating strategies for a multicultural or multinational site, although we focus on the distinct concept of a domestic foodservice business that serves a multicultural market

A Market Utility-Based Model for Capacity Scheduling in Mass Services

Only a small set of employee scheduling articles have considered an objective of profit or contribution maximization, as opposed to the traditional objective of cost (including opportunity costs) minimization. In this article, we present one such formulation that is a market utility-based model for planning and scheduling in mass services (mums), mums is a holistic approach to market-based service capacity scheduling. The mums framework provides the structure for modeling the consequences of aligning competitive priorities and service attributes with an element of the firm’s service infrastructure. We developed a new linear programming formulation for the shifts-scheduling problem that uses market share information generated by customer preferences for service attributes. The shift-scheduling formulation within the framework of mums provides a business-level model that predicts the economic impact of the employee schedule. We illustrated the shift-scheduling model with empirical data, and then compared its results with models using service standard and productivity standard approaches. The result of the empirical analysis provides further justification for the development of the market-based approach. Last, we discuss implications of this methodology for future research

A novel RNA in situ hybridization assay for the long noncoding RNA SChLAP1 predicts poor clinical outcome after radical prostatectomy in clinically localized prostate cancer.

Long noncoding RNAs (lncRNAs) are an emerging class of oncogenic molecules implicated in a diverse range of human malignancies. We recently identified SChLAP1 as a novel lncRNA that demonstrates outlier expression in a subset of prostate cancers, promotes tumor cell invasion and metastasis, and associates with lethal disease. Based on these findings, we sought to develop an RNA in situ hybridization (ISH) assay for SChLAP1 to 1) investigate the spectrum of SChLAP1 expression from benign prostatic tissue to metastatic castration-resistant prostate cancer and 2) to determine whether SChLAP1 expression by ISH is associated with outcome after radical prostatectomy in patients with clinically localized disease. The results from our current study demonstrate that SChLAP1 expression increases with prostate cancer progression, and high SChLAP1 expression by ISH is associated with poor outcome after radical prostatectomy in patients with clinically localized prostate cancer by both univariate (hazard ratio = 2.343, P = .005) and multivariate (hazard ratio = 1.99, P = .032) Cox regression analyses. This study highlights a potential clinical utility for SChLAP1 ISH as a novel tissue-based biomarker assay for outcome prognostication after radical prostatectomy