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A product or service usually has multiple measurable characteristics, and its performance on different measures may vary and may change over time. Multi-criterion and multi-period performance benchmarking presents a challenge for management to determine performance gaps among comparable products or services. The purpose of this paper is to propose a new performance benchmarking method to address this challenge.

The author develop this method by formulating two benchmarking functions: a differentiation function based on Shewhart average and standard deviation charts to distinguish the performance of products or services on a single measure, and a categorization function to classify each product’s or service’s overall performance across all measures. By systematically removing the lowest-performing products or services from comparison, the author use these functions iteratively to detect performance gaps.

Using this method, the author find performance gaps in each of three benchmarking applications of airports, hotels, and minivans, although a number of performance gaps are not obvious from the raw data.

This benchmarking study focuses on the quantifiable outcome performance of products and services.

This benchmarking method is generic and applicable to most products and services. It is robust not only for discovering performance gaps, but also for providing useful insights for managers to prioritize improvement efforts on individual performance measures.

The novelty of this benchmarking method lies in that it can not only find the “best overall” products or services for all performance measures, but can also pinpoint the “best-in-class” products or services as well as performance gaps for each performance measure. In addition, this paper presents several original ideas for performance benchmarking, including: using the control limits of Shewhart control charts to categorize performance gaps, systematically removing the lowest-performing products or services from comparison for the purpose of detecting hidden performance gaps, and using symbolic expressions to integrate benchmarking results from all measures and to show all performance gaps intuitively.

The Program for International Student Assessment (PISA) measured 15-year-olds’ performance in mathematics, reading, and science. The purpose of this paper is to use the assessment results of PISA 2006, 2009, and 2012 to benchmark the compulsory education performance of 65 countries and economies with emphasis on two benchmarking steps: identifying benchmarks and determining performance gaps.

The authors use a multi-criterion and multi-period performance categorization method to identify a group of best performers as benchmarks. Then, the authors use two-sample t-tests to detect against benchmarks whether each country or economy has significant performance gaps on individual performance measures.

Based on the mean scores of three assessment subjects in PISA 2006, 2009, and 2012, six best performers (Top-6) are identified from 65 participating countries and economies. In comparison with Top-6’s weighted averages, performance gaps are found for most countries and economies on the mean score of each subject, the percentage of top-performing students in all three subjects, and the percentage of lowest-performing students in each subject.

For compulsory education systems around the world, this paper provides an original categorization of performance based on the results of three PISA cycles, and provides new insights for countries and economies to prioritize improvement efforts to increase average performance, pursue excellence, and tackle low performance. For benchmarking applications involving multi-criterion and multi-period data, this paper presents a novel method of using statistical control charts to identify benchmarks and then using two-sample t-tests to determine performance gaps on individual performance measures.

Although software systems used to automate business processes have been becoming rather advanced, the existing practice of developing and modifying graphical process models in those software systems is still primitive: users have to manually add, change, or delete each node and arc piece by piece. Since such manual operations are typically tedious, time‐consuming, and prone to errors, it is desirable to develop an alternative approach. This paper aims to address this issue.

In this paper, a novel, human‐understandable process manipulation language (PML) for specifying operations (e.g. insertion, deletion, merging, and split) on process models is developed. A prototype system to demonstrate PML is also developed.

The paper finds that manipulation operations on process models can be standardized and, thus, can be facilitated and automated through using a structured language like PML.

PML can improve manipulation operations on process models over the existing manual approach in two aspects: first, using PML, users only need to specify what operations are to be performed on process models, and then a computer carries out specified operations as well as performs other routine operations (e.g. generating nodes and arcs). This feature minimizes user effort to deal with low‐level details on nodes and arcs. Second, using PML, users can systematically specify operations on process models, thus reducing arbitrary operations and problems in process models.

Process mapping is used to articulate the activities and procedures of business entities in a graphical way as pictorial images readily convey considerable information. The objective of this research is to provide evidence and a methodology to assist organizations in evaluating the early stages of their process mapping efforts.

A review of literature identifies key characteristics of transparency (process visibility) related to process mapping. Quizzes and surveys are used to study the impact of process mapping on transparency in an employee training session.

The paper finds that process mapping increases transparency between 5 percent and 27 percent for the applications discussed in this paper.

The research presumes that better understanding and recall of the company's business processes equates to higher transparency. This research study is limited to one field test, organization, and process mapping methodology. These limitations should be considered when extrapolating the results to other organizations.

The methodology outlined in this paper provides a way to measure the impact that formalizing (mapping) an organization's business processes and then using these maps to communicate the organization's business processes has on an individual employee's understanding and recall of those business processes. This methodology may help other organizations evaluate the early stages of their process mapping efforts.

A measurable definition of transparency is developed. A field study provides evidence that process mapping increases transparency and a methodology is shared for others to study the impacts of their process mapping efforts.

The following definitions and standards for food products have been adopted as a guide for the officials of this Department in enforcing the Food and Drugs Act. These are standards of identity and are not to be confused with standards of quality or grade; they are so framed as to exclude substances not mentioned in the definition and in each instance imply that the product is clean and sound. These definitions and standards include those published in S. R. A., F. D. 2, revision 4, and those adopted October 28, 1936.

Presents a special issue, enlisting the help of the author’s students and colleagues, focusing on age, sex, colour and disability discrimination in America. Breaks the evidence down into manageable chunks, covering: age discrimination in the workplace; discrimination against African‐Americans; sex discrimination in the workplace; same sex sexual harassment; how to investigate and prove disability discrimination; sexual harassment in the military; when the main US job‐discrimination law applies to small companies; how to investigate and prove racial discrimination; developments concerning race discrimination in the workplace; developments concerning the Equal Pay Act; developments concerning discrimination against workers with HIV or AIDS; developments concerning discrimination based on refusal of family care leave; developments concerning discrimination against gay or lesbian employees; developments concerning discrimination based on colour; how to investigate and prove discrimination concerning based on colour; developments concerning the Equal Pay Act; using statistics in employment discrimination cases; race discrimination in the workplace; developments concerning gender discrimination in the workplace; discrimination in Japanese organizations in America; discrimination in the entertainment industry; discrimination in the utility industry; understanding and effectively managing national origin discrimination; how to investigate and prove hiring discrimination based on colour; and, finally, how to investigate sexual harassment in the workplace.

Globalisation is generally defined as the “denationalisation of clusters of political, economic, and social activities” that destabilize the ability of the sovereign State to control activities on its territory, due to the rising need to find solutions for universal problems, like the pollution of the environment, on an international level. Globalisation is a complex, forceful legal and social process that take place within an integrated whole with out regard to geographical boundaries. Globalisation thus differs from international activities, which arise between and among States, and it differs from multinational activities that occur in more than one nation‐State. This does not mean that countries are not involved in the sociolegal dynamics that those transboundary process trigger. In a sense, the movements triggered by global processes promote greater economic interdependence among countries. Globalisation can be traced back to the depression preceding World War II and globalisation at that time included spreading of the capitalist economic system as a means of getting access to extended markets. The first step was to create sufficient export surplus to maintain full employment in the capitalist world and secondly establishing a globalized economy where the planet would be united in peace and wealth. The idea of interdependence among quite separate and distinct countries is a very important part of talks on globalisation and a significant side of today’s global political economy.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

Outlines previous research relevant to the risks involved in residential mortgages and suggests some reasons for the gap between theory and market practice. Develops a model which adds household income, ability to pay problems and mortgage underwriting constraints to the standard pricing models, using a combination of Monte Carlo simulation and the backward finite difference method to apply it to data on house prices, income and interest rates for 62 US metropolitan areas. Discusses the results which suggest that prepayment risk dominates default risk in all except very low growth housing markets. Adds that increasing loan‐to‐value levels decrease loan values in low growth markets, slightly increase them in high growth/low volatility markets (due to decline in prepayment risk), but have little impact on high growth/high volatility markets (because they are offset by changes in default and prepayment costs). Considers the practical implications of the findings, e.g. for portfolio managers.

This paper aims to examine the extent to which Business Intelligence and Big Data feature within academic research in hospitality and tourism published until 2016, by identifying research gaps and future developments and designing an agenda for future research.

The study consists of a systematic quantitative literature review of academic articles indexed on the Scopus and Web of Science databases. The articles were reviewed based on the following features: research topic; conceptual and theoretical characterization; sources of data; type of data and size; data collection methods; data analysis techniques; and data reporting and visualization.

Findings indicate an increase in hospitality and tourism management literature applying analytical techniques to large quantities of data. However, this research field is fairly fragmented in scope and limited in methodologies and displays several gaps. A conceptual framework that helps to identify critical business problems and links the domains of business intelligence and big data to tourism and hospitality management and development is missing. Moreover, epistemological dilemmas and consequences for theory development of big data-driven knowledge are still a terra incognita. Last, despite calls for more integration of management and data science, cross-disciplinary collaborations with computer and data scientists are rather episodic and related to specific types of work and research.

This work is based on academic articles published before 2017; hence, scientific outputs published after the moment of writing have not been included. A rich research agenda is designed.

This study contributes to explore in depth and systematically to what extent hospitality and tourism scholars are aware of and working intendedly on business intelligence and big data. To the best of the authors’ knowledge, it is the first systematic literature review within hospitality and tourism research dealing with business intelligence and big data.