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Statistical quality control charts cannot indicate explicitly whether there is any special disturbance in the manufacturing process. pattern recognition scheme can solve this problem. The simultaneous control of two or more variables is necessary when the quality of the product depends on the joint effect of these variables. Studies the combination patterns of random and random, shift and cycle, trend and cycle, and trend and shift for two variables. Proposes a T² control chart and uses simulation to determine pattern diagnostic characteristics for these combinations. The pattern diagnostic characteristics studied are window size, zone boundary, and zone representation. The results indicate that window size 20 is appropriate for these particular parameters, equal probability and the highest percentage alternative are adopted as the zone boundary and the zone representation, respectively. The sensitivity analysis of the pattern parameters indicates the pattern diagnostic is robust for changes in the parameter values.

The need for more intensive utilization of expensive and complex equipment has brought about a considerable expansion of shift working. This expansion has been not so much in the number of people on shift work as in the variety of categories of staff who are asked — or required — to work shifts, and in the diversification of patterns of shift working.

In the five years that have elapsed since Sloane reported on the changing patterns of working hours in Britain, the rate of change has increased and the pattern of change has become more complex. This paper sets out to update thinking about patterns of change, proposes a research model and poses a number of research issues. Since terminology can be confusing, we start with some definitions.

The purpose of this paper is to develop a control chart pattern recognition methodology for monitoring the weekly customer complaints of outsourced information technology-enabled service (ITeS) processes.

A two-step methodology is used to classify the processes as having natural or unnatural variation based on past 20 weeks' customer complaints. The step one is to simulate data on various control chart patterns namely natural variation, upward shift, upward trend, etc. Then a deep learning neural network model consisting of two dense layers is developed to classify the patterns as of natural or unnatural variation.

The validation of the methodology on telecom vertical processes has correctly detected unnatural variations in two terminated processes. The implementation of the methodology on banking and financial vertical processes has detected unnatural variation in one of the processes. This helped the company management to take remedial actions, renegotiate the deal and get it renewed for another period.

This study provides valuable information on controlling information technology-enabled processes using pattern recognition methodology. The methodology gives a lot of flexibility to managers to monitor multiple processes collectively and avoids the manual plotting and interpretation of control charts.

The application of control chart pattern recognition methodology for monitoring service industry processes are rare. This is an application of the methodology for controlling information technology-enabled processes. This study also demonstrates the usefulness of deep learning techniques for process control.

Quality control charts are statistical process control tools aimed at monitoring a (manufacturing) process to detect any deviations from normal operation and to aid in process diagnosis and correction. The information presented on the chart is a key to the successful implementation of a quality process correction system. Pattern recognition methodology has been pursued to identify unnatural behaviour on quality control charts. This approach provides the ability to utilize patterning information of the chart and to track back the root causes of process deviation, thus facilitating process diagnosis and maintenance. Presents analysis and development of a statistical pattern recognition system for the explicit identification of unnatural patterns on control charts. Develops a set of statistical pattern recognizers based on the likelihood ratio approach and on correlation analysis. Designs and implements a training algorithm to maximize the probability of identifying unnatural patterns, and presents a classification procedure for real‐time operation. Demonstrates the system performance using a set of newly defined measures, and obtained results based on extensive experiments illustrate the power and usefulness of the statistical approach for automating unnatural pattern detection on control charts.

Content analysis of search engine user queries is an important task, since successful exploitation of the content of queries can result in the design of efficient information retrieval algorithms of search engines, which can offer custom‐tailored services to the web user. Identification of topic changes within a user search session is a key issue in content analysis of search engine user queries. The purpose of this study is to address these issues.

This study applies genetic algorithms and Dempster‐Shafer theory, proposed by He et al., to automatically identify topic changes in a user session by using statistical characteristics of queries, such as time intervals and query reformulation patterns. A sample data log from the Norwegian search engine FAST (currently owned by overture) is selected to apply Dempster‐Shafer theory and genetic algorithms for identifying topic changes in the data log.

As a result, 97.7 percent of topic shifts and 87.2 percent of topic continuations were estimated correctly. The findings are consistent with the previous application of the Dempster‐Shafer theory and genetic algorithms on a different search engine data log. This finding could be implied as an indication that content‐ignorant topic identification, using query patterns and time intervals, is a promising line of research.

Studies an important dimension of user behavior in information retrieval.

Popular literature argues that successive generations are experiencing more job changes and changes of employer. The “new careers” literature also proposes that career mobility patterns are becoming more diverse as people engage in more downward and lateral job changes and changes of occupation. The purpose of this paper is to test these assertions by comparing the career mobility patterns across four generations of workers.

The authors analyzed the career mobility patterns of four generations of Canadian professionals (n=2,555): Matures (born prior to 1946); Baby Boomers (1946-1964); Generation Xers (1965-1979) and Millennials (1980 or later). Job mobility, organizational mobility and the direction of job moves were compared across groups through analysis of variance.

Significant differences were observed in job mobility and organizational mobility of the various generations, with younger generations being more mobile. However, despite significant environmental shifts, the diversity of career patterns has not undergone a significant shift from generation to generation.

This is the first quantitative study to examine shifting career mobility patterns across all four generations in today’s workplace. The authors extend previous research on generational differences in job mobility by using novel measures of career mobility that are more precise than extant measures.

The purpose of this paper is to explore the issues in the shiftworking literature and to apply these to an administrative environment.

The scope of the paper is the issue of health problems in shiftworkers in administrative environments. The method was to use case study organisations which had introduced shiftwork and discover from semi‐structured interviews of staff what the effects had been.

Given the choice, employees opted for shiftwork, especially women and especially for a night or evening shift; anticipated problems of absenteeism and labour turnover and low performance related to health issues were not present.

The design was limited to two organisations which gave access; this may have been because they were able to report positive outcomes. A broader survey may uncover negative aspects which this paper could not.

The concerns over health cannot be transferred to an administrative environment. This may encourage organisations to introduce more shift patterns, given full employee involvement from the outset. Shift premia, so common elsewhere, and a concern to cost‐conscious managers were not paid.

The concerns over health uncovered by previous research on shiftwork are not present in administrative environments.

Debates a controversial issue in healthcare management, that is, whether internal rotation (day‐night) or permanent night shifts is an appropriate shift system for nursing staff. A multidisciplinary approach draws together international research from the fields of occupational psychology, management, ergonomics and medicine. Explores evidence on sleep, physical and mental health, job satisfaction, performance, absenteeism, and social and domestic disruption, all important factors in considering appropriate shift patterns. Suggests that both nurse choice (or non‐choice) of shift and adjustment, or otherwise, of circadian rhythms are important causal factors influencing the debate. As no unequivocal picture emerges, recognizes some of the real and potential limitations of a paper of this kind; however, the balance of argument tends to favour the maintenance of permanent night shift nurses as opposed to the further extension of internal rotation systems. This is especially the case as many nurses will still be given a choice of shift pattern which may, in itself, negate some of the potential ill‐effects of night working. Decisions further to extend internal rotation may, in the light of the complex, ambiguous and equivocal evidence, be informed by partial knowledge and influenced by a managerial perspective.

This study aims to compare the career patterns of Matures, Baby Boomers, Generation Xers and Millennials over the various stages of their careers to determine whether there have been notable shifts away from the “traditional” career model characterized by long‐term linear, upward career movement, toward a “modern” career model characterized by increased job mobility, organizational mobility and multi‐directional career movement.

The retrospective career accounts of 105 Canadians were gathered through review of résumé information and semi‐structured interviews. The job changes and organizational changes experienced by each respondent in each five‐year career period (e.g. age 20‐24, 25‐29) and the direction of job changes (i.e. upward, downward, lateral or change of career track) were recorded. The generations were compared statistically on each of these measures through analysis of variance (ANOVA).

Significant inter‐generational differences were observed on all variables of interest, but the differences were largely restricted to the age 20‐24 and 30‐34 career stages.

The study relied on a small sample because of the qualitative nature of the data collection. The sample was also exclusively Canadian. The results should therefore be interpreted with care and the research should be replicated with different types of respondents and in different cultural contexts.

The research demonstrates to employers that the younger generations change jobs and employers at a greater rate than previous generations and that they are more willing to accept non‐upward career moves. Recruiting and retaining young employees will therefore require a different approach than was used for previous generations.

The use of retrospective accounts allowed for the comparison of generations within various career stages. This overcomes a significant limitation of cross‐sectional studies of generational phenomena by simultaneously considering life‐cycle and generational cohort effects.