In-house Jobs Research Articles

A Review of Gender in the 21st Century: Fighting Dangerous Stereotypes

Gender is a condition of being a male or female. Much of the time, it is generally defined by social and social distinctions rather than biological differences. Gender stereotype generalizations are currently present for life. Even though a disposition to mess up a part of the present gender stereotypes-related platitude occurs due to late unreasonably being insufficient to deal with the issues that comprise gender lays out. Whereas generally, females wind up being casualties of gender stereotypes, males experience the adverse effects of criminal offenses associated with maleness. Women's works tend to be predominantly traditional and less prestigious, while personalities are predominantly shy and passive characterization. Women are primarily engaged in domestic and in-house jobs, while men are more likely to exist in specialist facilities. There appears to be a systematic under-representation of women, regardless of whether we consider the text or images. The study shows a point of view for the effect of gender stereotypes and the progression of female stereotypes in the 21st century.

Extinction or evolution?

Since the 1990s, outsourcing, streamlining and technologisation have induced profound changes in the content, organisation and location of translators’ work. Nevertheless, due to the scarcity of longitudinal research, such changes must typically be pieced together from individual studies. The present paper adopts a novel approach: analysing data from a survey in which the respondents (n=223) could report on one current and two previous in-house positions, we provide an overview of the changes in in-house translators’ work in Finland from 1995 to 2018. Combining quantitative and qualitative methods, we consider 1) indications of outsourcing and restructuring, 2) changes in responsibilities and 3) changes in physical location and organisational position. The responses indicate some decrease in in-house jobs and a greater variety in responsibilities. There is also an increase in teleworking and indications of complex organisational structures, although translation teams remain common. On the whole, in-house translators appear an evolving rather than an endangered professional group.

Approximation algorithms for the min-max regret identical parallel machine scheduling problem with outsourcing and uncertain processing time

We consider the robust (min-max regret) version of identical parallel machine scheduling problem, in which jobs may be outsourced to balance total cost against production efficiency. The total cost is measured in terms of the total completion time of jobs processed in-house and the cost of outsourcing the rest. Processing times of in-house jobs are uncertain and they are described as two types of scenarios: discrete and interval. The objective is to obtain a robust (min-max regret) decision that minimises the absolute deviation of total cost from the optimal solution under the worst-case scenario. We first prove the worst-case scenario for any feasible solution. For the interval scenario, we further prove that the maximum regret value can be obtained in polynomial time for any feasible schedule. We also prove that for any discrete scenario, the minimum total cost can be obtained in polynomial time. Since the problem with the interval scenario is strongly NP-hard, we then transform the problem into an equivalent robust single machine scheduling problem. Finally, we develop 2-approximation algorithms for the problem with discrete and interval scenarios, respectively. These results are helpful for bridging the scheduling theory and practice in identical parallel machining environments with outsourcing and uncertain processing times.

Production Scheduling considering Outsourcing Options and Carrier Costs

We consider a single-machine scheduling problem with outsourcing options in an environment where the cost information of the downstream is available via some information sharing technologies. The due date is assigned to the position differently from the traditional due date. Each job can be processed in-house or outsourced. Note that, for cost saving, as many due dates as the number of outsourced jobs should be canceled. An in-house job incurs a stepwise penalty cost for tardiness, and an outsourced job incurs an outsourcing cost. Thus, the objective is to minimize the total penalty and outsourcing cost minus the total profit from cost savings. We show that the problem is weakly NP-hard and investigate some polynomially solvable cases. Due to the high complexity of the dynamic programming, we developed heuristics and verified their performance through numerical experiments.

Enhancing the sustainability of employees' careers through training: The roles of career actors' openness and of supervisor support

Adopting a quasi-experimental design with four points in measurement, this study developed and tested a model whose variables represented key elements of the sustainable career process as captured in up-to-date thinking. The model posited that employees' openness to experience and supervisor support for training would lead to increases in employees' job performance and employability via learning as the result of an employer-sponsored training course. Training represented the contribution of the employer, who is the other key stakeholder in sustainable careers. The model was tested on 334 salespersons who attended an in-house job training course. Job performance and employability, as assessed by line managers, increased substantially and significantly following the training with respect to their pre-training levels, and learning as a result of the training mediated the relationships of openness to experience and supervisor support with the increases in job performance and employability. Contrary to expectations of a positive synergy, a substitution effect was found between openness and supervisor support in fostering learning as result of training, and subsequently, increases in job performance and employability. The study provided a comprehensive albeit short-term picture of the sustainable careers process as conceptualized in the theoretical literature. In addition, it illustrated the effectiveness of job training in the enhancement of employability. The implications of the study for theory and further research on sustainable careers and employability are discussed.

Outsourcing and rescheduling for a two-machine flow shop with the disruption of new arriving jobs: A hybrid variable neighborhood search algorithm

This paper addresses the two-machine flow shop outsourcing and rescheduling problem (TFSORP) in response to an unexpected arrival of new jobs, in which each job can be processed in the in-house shop or outsourced to a single subcontractor. An efficient schedule is constructed for the in-house jobs, and its performance is measured by the makespan. Each of the outsourced jobs requires paying an outsourcing cost. The objective is to minimize the sum of the in-house makespan and total outsourcing cost, subject to a limit on the number of original jobs processed by the subcontractor after disruption. To solve this NP-hard problem, a mixed integer programming formulation and helpful optimization properties are first established, and then a hybrid variable neighborhood search algorithm (HVNS) that incorporates one-dimensional array representation and three problem-specific neighborhood structures is developed. At the initialization stage, either of two well-designed constructive heuristics, i.e., job addition heuristic (JAH) and job removal heuristic (JRH) is employed. At the iterative search stage, an adaptive best-improvement procedure based on three neighborhood structures is devised to play the role of local search. An extensive experimental calibration for main factors in HVNS is carried out by a full-factorial design of experiments. To validate the calibrated HVNS, computational experiments are conducted upon the test suite of various instances. As demonstrated in the results, the calibrated HVNS gains the advantage over both the commercial optimizer and exhaustive approach in terms of computation time for small-sized instances, while it also outperforms an existing meta-heuristic algorithm and two canonical ones (based on the principles of genetic algorithm and simulated annealing) in the optimizing capability.

A Single-Machine Scheduling Problem with Uncertainty in Processing Times and Outsourcing Costs

We consider a single-machine scheduling problem with an outsourcing option in an environment where the processing time and outsourcing cost are uncertain. The performance measure is the total cost of processing some jobs in-house and outsourcing the rest. The cost of processing in-house jobs is measured as the total weighted completion time, which can be considered the operating cost. The uncertainty is described through either an interval or a discrete scenario. The objective is to minimize the maximum deviation from the optimal cost of each scenario. Since the deterministic version is known to be NP-hard, we focus on two special cases, one in which all jobs have identical weights and the other in which all jobs have identical processing times. We analyze the computational complexity of each case and present the conditions that make them polynomially solvable.

BUILDING AN EFFECTIVE SALES FORCE

Building an effective sales force starts with selecting good salespeople, but good salespeople are very difficult to find. The reason for this is that most sales jobs are very demanding and require a great deal from the salesperson. There are many different types of sales jobs. Before it can hire salespeople, each company must do a careful job analysis to see what particular types of selling and other skills are necessary for each sales job. One task of the market planner is to establish clear objectives each year for the entire sales force, for each region, each sales office, and each salesperson. Sales jobs are different from in-house jobs in some significant ways. Nevertheless, each company must continually work on building and maintaining an effective sales force using the following steps: recruitment, selection, training, compensation and evaluation of each salesperson.

Min–max regret version of a scheduling problem with outsourcing decisions under processing time uncertainty

We consider the min-max regret version of a single-machine scheduling problem to determine which jobs are processed by outsourcing under processing time uncertainty. The performance measure is expressed as the total cost for processing some jobs in-house and outsourcing the rest. Processing time uncertainty is described through two types of scenarios: either an interval scenario or a discrete scenario. The objective is to minimize the maximum deviation from optimality over all scenarios. We show that when the cost for in-house jobs is expressed as the makespan, the problem with an interval scenario is polynomially solvable, while the one with a discrete scenario is NP-hard. Thus, for the discrete scenario case, we develop a 2-approximation algorithm and investigate when the problem is polynomially solvable. Since the problem minimizing the total completion time as a performance measure for in-house jobs is known to be NP-hard for both scenarios, we consider the problem with a special structure for the processing time uncertainty and develop a polynomial-time algorithm for both scenarios.

OUTSOURCING DECISIONS IN m-MACHINE PERMUTATION FLOW SHOP SCHEDULING PROBLEMS WITH MACHINE-DEPENDENT PROCESSING TIMES

We consider m-machine permutation flow shop problems with an outsourcing option for a special case where each job's processing time equals the job's processing requirement plus a characteristic value of the machine. The objective is to minimize the sum of the performance measure for in-house jobs (the total completion time or the makespan) and the total outsourcing cost. We prove that two problems are polynomially solvable when the number of machines is fixed.

Outsourcing and scheduling for two-machine ordered flow shop scheduling problems

This paper considers a two-machine ordered flow shop problem, where each job is processed through the in-house system or outsourced to a subcontractor. For in-house jobs, a schedule is constructed and its performance is measured by the makespan. Jobs processed by subcontractors require paying an outsourcing cost. The objective is to minimize the sum of the makespan and the total outsourcing cost. Since this problem is NP-hard, we present an approximation algorithm. Furthermore, we consider three special cases in which job j has a processing time requirement pj, and machine i a characteristic qi. The first case assumes the time job j occupies machine i is equal to the processing requirement divided by a characteristic value of machine i, that is, pj/qi. The second (third) case assumes that the time job j occupies machine i is equal to the maximum (minimum) of its processing requirement and a characteristic value of the machine, that is, max{pj,qi} (min{pj,qi}). We show that the first and the second cases are NP-hard and the third case is polynomially solvable.

A Genetic-based Algorithm to Find Better Estimation of Non-Dominated Solutions for a Bi-objective Re-entrant Flowshop Scheduling Problem with Outsourcing

Abstract In this paper, we present a mathematical model for a flowshop scheduling problem with two machines in which each job visits both machines twice. Due to the strict due dates, tardiness is not allowable so the scheduler needs to choose the jobs for being processed in-house and therefore outsources the remaining jobs. This decision shall be made regarding two objective functions: minimization of total completion time for in-house jobs and minimization of outsourcing cost. Since the problem is NP-hard, we propose a genetic-based algorithm to find non-dominated solutions for large-sized problems. By defining efficient dominance properties rather than Pareto and a secondary criterion for making diversification in the population different from crowding distance, we focus our search on middle part of Pareto-front as we believe that the solutions located in this part are more interesting for the decision maker. We compare the quality of solutions found by our proposed algorithm with the simplest variant of NSGA-II. Although proposed algorithm is able to find limited number of non-dominated solutions, the quality of the solutions are improved significantly.

Two-machine flow shop scheduling problem with an outsourcing option

We consider a two-machine flow shop problem in which each job is processed through an in-house system or outsourced to a subcontractor. A schedule is established for the in-house jobs, and performance is measured by the makespan. Jobs processed by subcontractors require paying an outsourcing cost. The objective is to minimize the sum of the makespan and total outsourcing costs. We show that the problem is NP-hard in the ordinary sense. We consider a special case in which each job has a processing requirement, and each machine a characteristic value. In this case, the time a job occupies a machine is equal to the job’s processing requirement plus a setup time equal to the characteristic value of that machine. We introduce some optimality conditions and present a polynomial-time algorithm to solve the special case.

Knowledge and expertise for high-technology entrepreneurship: a tale of two sectors

The last three decades have witnessed fundamental structural changes in many western economies. Traditional sectors have seen dramatic reductions in manpower needs and large organisations have reorganised and rationalised. As in-house jobs have disappeared, opportunities for entrepreneurial, small firms to meet the outsourcing needs of growing numbers of organisations have increased dramatically. Agencies and government departments concerned with economic development and boosting levels of new firm formation are keen to encourage would-be entrepreneurs to establish ventures. While the provision of external support and the role of mentors through the venture creation process are valuable inputs into the process, the entrepreneur is arguably the most important resource. Understanding the role of the entrepreneur in the start-up process, and the knowledge and skills which he requires to perform his role effectively, will assist those seeking to enhance levels of new venture creation. This paper explores the sources and development of knowledge and skills in a group of 94 high-technology small firm founders in software and electronics. Marked differences are apparent in the background and experiences of entrepreneurs in the two sectors, as the founders have travelled contrasting routes to arrive at the entrepreneurial starting line. Findings are of significance for agencies supporting technology-based firm development and would-be entrepreneurs considering enterprise creation opportunities.

`Portfolio Workers': Autonomy and Control amongst Freelance Translators

Recent literature has begun to disaggregate groups of the `self-employed without employees' to examine in greater detail what determines their working conditions. This article continues this trend by presenting the findings of a survey of professional translators and discussing their status as `homeworkers', `teleworkers', and `portfolio workers'. It reveals that freelance translators enjoy higher levels of autonomy and control over their working conditions than other comparable self-employed groups. This is largely because the nature of their expertise and their relationship with clients create inelasticities in the supply of their skills. The more successful are then able to use their market position to exert substantial control over areas like pay and deadlines. In addition, the lack of a traditional career structure means that many translators have actively chosen freelance work and that even those who were originally forced into it would not now take an in-house job. The article concludes that labour market characteristics are a key factor in determining differences in working conditions between various groups of `portfolio workers'.

Recruitment Source Research: Current Status and Future Directions

The effectiveness of different recruitment sources for new employees has been the topic of speculation and research for over 50 years. Effectiveness has primarily been assessed by examining turnover/job survival rates and job performance. As reported in most narrative reviews and all five quantitative reviews, referrals by current personnel, in-house job postings, and the re-hiring of former employees are the most effective sources. Walk-ins have been slightly less effective, and the least effective sources are newspaper ads, school placement services, and employment agencies (government/private). Over these 50 years, six explanations for this pattern have been offered. They are summarized and evaluated here. The practical usefulness of recruiting from effective sources is estimated, based on the effect sizes from our meta-analysis. Finally, suggestions for future research are made.

Job Analysis: A Local Government's Experience

Job analysis has been described by some as the basic activity of human resource management.(1) Others, like Riggio,(2) suggest that job analysis is the starting point for nearly all personnel functions. In local government, informal job analysis occurs regularly when a department head tells an elected official about the need for a new position or when a supervisor making a hiring decision must decide what questions to ask potential hirees. Such activities do not simply occur in a vacuum. Indeed, informal job analysis is probably the norm in many small local governments where the resources to conduct a formal job analysis do not exist. Deciding to conduct a formal job analysis is rather like deciding to clean out your attic. Generally, you have put it off so long that you are now forced to do it and you know there will be family squabbles about what you can get rid of and what you must keep. The Mobile County, AL Personnel Department, a civil service agency representing about 5,000 employees in 20 separate governmental entities, opted to conduct an analysis of some 500 job classifications. Formal job analysis had been regularly conducted for the validation of selection and promotion procedures in certain critical areas using a model proposed by Menne, McCarthy and Menne.(3) The decision was made to undertake an analysis of the entire classification system in an effort to address employee concerns in a variety of areas. Most of the concerns brought by employees dealt with improper classification and lack of perceived internal pay equity. The Mobile County Personnel Department also saw an opportunity to expand the validation of selection and promotion procedures, reduce the number of job classifications and to enhance the performance appraisal system. It became apparent to the department staff that a unified job analysis approach would be the most efficient, economical and practical means of addressing all concerns while still adhering to necessary legal and technical standards. Development of the Job Analysis Questionnaire A review of a number of existing job analysis instruments was conducted. These included the Critical Incident Technique(4) and the Position Analysis Questionnaire.(5) In our search to find an approach that might meet all our needs we strongly considered the Versatile Job Analysis System (VERJAS) as described by Bemis, Belenky and Soder.(6) These authors demonstrated that a comprehensive approach to job analysis was practical and that such data could be applied to a wide range of personnel management decisions. In the end, however, we decided to develop our own job analysis instrument. Some of the existing instruments were simply too long or complicated to be used for a variety of job classifications. Others required too much creative narrative writing on the part of employees. A major consideration was that the instrument should lend itself to data analysis by computer The ratio of project staff workers to employees necessitated this, since the goal was to survey all employees and not just a sample of workers from each job classification. The development of the in-house job analysis questionnaire took approximately six months. Quantification of data, where practical, was given high priority to ensure as much objectivity as possible. Attempting to make the document readable for a wide range of employees was given much attention. Customized data analysis programs were written and tested. Much effort was devoted to concerns addressed in the Uniform Guidelines on Employee Selection Procedures.(7) The final questionnaire consisted of eight sections as listed in Table 1. Job duties consisted of broad dimensions of work associated with various jobs. In order to help employees organize their jobs, a list of job duties was provided to employees. The list was generated from job descriptions and other documents on file with the department. The list consisted of job duties like Typing, Firefighting, Counseling and Testing. …