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The operating theater is one of the most expensive units in the hospital, representing up to 40% of the total expenses. Because of its importance, the operating room scheduling problem has been addressed from many different perspectives since the early 1960s. One of the main difficulties that has reduced the applicability of the current results is the high variability in surgery duration, making schedule recommendations hard to implement. In this work, we propose a time-indexed scheduling formulation to solve the operational problem. Our main contribution is that we propose the use of chance constraints related to the surgery duration’s probability distribution for each surgeon to improve the scheduling performance. We show how to implement these chance constraints as linear ones in our time-indexed formulation, enhancing the performance of the resulting schedules significantly. Through data analysis of real historical instances, we develop specific constraints that improve the schedule, reducing the need for overtime without affecting the utilization significantly. Furthermore, these constraints give the operating room manager the possibility of balancing overtime and utilization through a tuning parameter in our formulation. Finally, through simulations and the use of real instances, we report the performance for four different metrics, showing the importance of using historical data to get the right balance between the utilization and overtime.

Mitigating the adverse effects of uncertainty in appointment systems, arising from heterogeneous patient needs and preferences, is critical to the effective use of scarce medical resources and patient satisfaction. This study addresses an online scheduling problem with multiple servers and consideration of patient preference for physicians and their appointment times. The receptionist immediately determines whether a request should be accommodated and offers an appointment time slot for each accepted patient request. The patient may reject an undesirable appointment time slot with a certain probability, or may accept it, but the no-show probability will be higher. A stochastic overbooking model is formulated to maximize the expected profit, which is defined as the revenue generated from accepted requests minus the cost incurred by patients waiting and physicians’ overtime. A myopic scheduling policy is developed based on certain structural properties of the objective function. This study advances the study of appointment systems by generating a non-unimodal profit evolution. Moreover, both the decision of accommodating more requests for certain slots and scheduling of appointments depend on the patient choice rather than the patient type. Further, computational experiments and analysis offer valuable insights into performance improvement in outpatient clinics.

Highlights • An RT process simulation model aided managers with resource planning decisions. • Several scenarios could easily be evaluated without affecting the clinical work. • Starting vacation periods for preparations prior to treatment was most beneficial., Purpose Radiotherapy (RT) resources need to be used wisely to balance workload and patient throughput. There are no known strategies on how to plan resource use around longer vacation periods to avoid patient waiting times. We created a simulation model over the RT workflow to evaluate different scenarios for this purpose. Materials and Methods The simulation model mimics a large modern RT department in Sweden. It was based on real data on patient referral patterns and resource use extracted from clinical systems (3666 treatment courses). Workshops with managers and staff were held to investigate nine different scenarios for the summer vacation period including one scenario to validate the model. Different capacity reductions, vacation period lengths and timing of the vacation periods between the preparatory part of the RT workflow and the treatment part were evaluated. Results For an eight-week period, resource utilization was predicted to be high both before and after the vacation period regardless of timing. However, more patients would be waiting with completed preparations with simultaneous vacation periods than when the preparatory part started one-two weeks prior to the treatment part. With shorter vacation periods, treatment would require overtime during the vacation period with higher levels of patients waiting compared to an eight-week scenario. Conclusions Our proposed strategy aided managers to identify a preferred scenario for the summer vacation period with the preparatory part starting one-two weeks prior to the treatment part for an eight-week vacation period. This can help other RT departments to plan for similar situations.

Background The literature identifies a strong relationship between mental health and income, but there is little research that clarifies the directional association between household income and self-perceived mental health (SPMH) overtime either at between-perso+n or within-person levels. This study investigates whether higher income predicts better SPMH overtime and poor SPMH predicts lower income overtime both at between-person or within-person levels. Methods Data analyzed was from the Montreal Southwest Social and Psychiatric Epidemiology Catchment Area study (ZEPSOM), a longitudinal community-based cohort. The baseline survey was conducted in 2007/8 with follow-up every two years. We traced a total of 3464 participants over a period of 8 years. To examine the associations between income and SPMH at both between-person or within-person levels, cross-lagged panel models (CLPMs) and random intercept cross-lagged panel models (RI-CLPMs) were used. Gender and age effects were examined using multiple group analyses. Complete case analyses evaluated the findings’ robustness. Results At between-person levels, higher household income predicted higher SPMH, but not vice versa. These associations were stronger among men and older adults. At within-person levels, higher income did not predict higher SPMH. No significant gender- or age- group differences were observed. Complete case analyses supported the findings. Limitations Loss to follow-up may affect the generalizability of the research findings. Conclusions This study suggests that higher household income predicts higher SPMH at between-person levels. Policy and programs aiming at promoting mental health should focus on low-income individuals, especially men and older adults.

Creativity is a key influential factor contributing to organizations’ development. The contribution of creativity provides many crucial benefits to organizations and employees: high satisfaction, new ideas, strong teams, increasing innovation. To explore creativity as a hidden development factor, a random sample of 212 individuals in the private and public sectors were used to collect primary data. Logit regressions were specified to reveal the role of creativity in organizational development and job satisfaction for employees. We show that creativity is the only such driving factor able to decrease stress and lead to success and development together with high satisfaction levels. Specifically, job initiatives, workload pressure, creative change and overtime are shown to particularly affect stress levels. Job-creativity and use of skills have a higher impact on satisfaction followed by distance from work, freedom of actions and wages and other benefits. Further, job training and changes in management proved to be statistically insignificant.

The goal of this work is to discuss a production inventory model for deteriorating items with nonlinear price and linear stock dependent market demand along with an overtime production opportunity. The corresponding optimization problem is articulated mathematically and hence solved by using lingo software. To examine the proposed nonlinear optimization problem’s significance, one numerical example is deliberated. A sensitivity analysis is accomplished on the basis of the systematic changes of the system parameters. As a final point, based on the accomplished analysis an effectual conclusion is reflected.

There is a growing body of scientific evidence that demonstrates a negative relationship between commuting and wellbeing. However, many of the existing studies have some limitations with respect to geographical scope, the control variables included, or the operationalisation of either wellbeing or commuting. In this contribution, we consider weekly commuting hours (WCH) per employed individual. Furthermore, we combined 13 variables on physical condition, weariness, and mental condition in a new index for wellbeing. Thanks to the data from the large-scale European Working Conditions Survey from 2015, we were able to cover 35 European countries. A multilevel multiple linear regression model was developed with control variables for factors with a known influence on wellbeing, random intercepts per country, and random slopes for the estimated WCH effect per country. Our results confirm that more time spent on commuting is negatively associated with wellbeing, although the effect size of WCH on wellbeing is relatively small when compared to ageing, education level, frequently working overtime, and experiencing harassment or discrimination at work. The multilevel approach reveals relevant differences between European countries with respect to the general level of wellbeing and the effect of WCH. Nevertheless, in all the countries included in our analysis the relationship between WCH and wellbeing is slightly negative.

We propose that due to the decreased spectrum of available strategies (i.e., social simplicity) and simplified mechanisms of value creation (i.e., causal clarity) associated with a greater reliance on data-driven decisions in highly competitive and specialized industries, the positive effects of social capital for data analytics on firm performance will diminish when firms predominantly adopt data-driven decision-making in deploying human resources. Alternatively, the positive effect associated with social capital in data analytics is more profound when moderated by intuition-based (i.e., idiosyncratic knowledge) decision-making for managing HR selections. To test our hypotheses, we observed 30 major league baseball (MLB) teams over 6 years from 2009 to 2014 as the early phase of the ‘big data era’ that began as a result of PITCHf/x tracking systems in all MLB stadiums being implemented. Our findings suggest that the introduction of the system to all ballparks and resulting dispersion of specialized human capital across this industry facilitates firm specificity of data analytic knowledge to become generic overtime.

The ‘competitive threat’ theoretical model leads to the expectation that flows of documented and undocumented immigrants, economic downturns, and spread of conservative-nationalist ideologies would increase opposition to immigration. Recent studies on attitudes toward immigrants in American society do not show any increase in anti-immigrant sentiment. In the present study, we use data from the General Social Surveys (GSS) and American National Election Survey (ANES) to study change in opposition to immigration between 1996 and 2018. The findings obtained from the two data sources are strikingly similar and lead to the following conclusions. First, opposition to immigration had steadily and monotonously declined throughout the period. Second, the decline is evident even after considering variations and changes in the composition of the population, shifts in political ideologies, regional variations and cohort replacement. Third, the trend of decline in opposition to immigration takes a linear form. Fourth, opposition to immigration is stronger among Republicans and Independent voters than among Democrats. Fifth, the overtime decline in opposition to immigration was evident mostly among supporters of the Democratic Party increasing the division along party lines. The findings suggest that immigration is becoming a major political issue that is steadily polarizing American society.

As the number of competitors in the global marketplace is increasing very fast, it is essential for companies to reduce their lead-time to be sustainable game players. The objectives of this research are to a) improve the layout of a job shop production plant and b) enhance the flow of material from one station to another station to reduce lead times and enhance energy management. This paper focuses on a high-temperature heat treatment tooling manufacturer located in Northeast Indiana, USA. It found that the facility layout at the company was not optimal and over the past several decades, machines and equipment have been purchased and placed wherever there was room to place them. There was a significant amount of materials that are being back-tracked and moved by personnel, ultimately taking longer to produce the parts. The overall aspect of this research was to come up with an efficient robust system to improve the material flow throughout the manufacturing process and to ultimately reduce lead times to improve customers’ satisfaction and enhance energy management. For this purpose, the collective system design methodology integrated with systematic layout planning technique is applied to recognize systems’ needs and find possible scenarios based on activity relationships analysis, adjacency of operations, and total closeness ratings. Through the relationship activity diagram, the importance of adjacency among operations was assessed. Analysis on minimizing the travel distance and material handling along with conducted energy assessments verified that there are significant reductions in feet travelled per day and substantial increases in energy savings. Implementing such a layout improvement project resulted in a 16.66 % up to 33% reduction in lead-time of products (heat treating baskets), significant decreases in weekly overtime hours, and considerable enhancements in energy usage.

Current knowledge of benefits management is mostly limited to single organisations. This paper investigates benefits management applicable to large university-industry collaboration programs – a particular form of inter-organisational relationship. It presents a holistic, structured and customisable framework for how benefits can be managed, using the structured analysis and design technique. The research has been informed and validated in a major case study. The case study involved a R&D collaboration between a university and a large industry in Portugal over a six-year period with a total investment of more than 70 million Euros. The paper discusses the challenges of implementing benefits management among two organisations who have distinct and sometimes competing long-term benefits. This empirical research corroborates current theoretical approaches to benefits management and presents a number of new insights on how challenges may be effectively managed from a technical and social perspective, for example, the ownership of benefits realisation should change overtime, from Program Mangers to Line Managers of each organisation partner. Finally, the proposed BM.UIC framework can be used as starting point for development of a systematic benefit management process in any major project and program.

Studies on the etiology of behavioral problems often involve interference in the animal's routine or reliance on owners' self-reports like surveys. Gathering data from videos posted on social media, a technique coined ‘video mining’, offers novel opportunities to study the animal's behavior in their home environment remotely and with minimal disturbance. We use this technique on companion parrots, for whom inadequate captive environment and lack of social contact may cause various behavioral problems, with feather-damaging behavior as the most salient issue. Videos posted on YouTube were collected for feather-damaged (n = 36) and species-matched control parrots (n = 26). We scored plumage condition and recorded the parrot's characteristics: genus, sex, age, origin, and other behavioral problems. We also scored environmental characteristics: owner type, valence of human-animal interaction, presence of other parrots, presence of other companion animals, cage location and size, environmental enrichment with the provision of foraging, chewable and non-chewable devices, and type of feed. Finally, possible interventions against feather damage and their visible effects were recorded. The probability of feather damage was significantly influenced by several predictors (P = 0.001), with the presence of non-bird companion animals in the household and the provision of vegetables and fruits in the diet, foraging devices and chewable devices all reducing the risk of feather damage. Family-owned parrots were less likely to be feather-damaged, and women-owned parrots were more likely to be feather-damaged, although this finding could be biased by the type of person willing to share videos, to adopt a feather-damaged parrot, or other confounding variables. The various interventions attempted by owners (rehoming, conspecific, environmental enrichment, drug, collar, or combinations of these) resulted in plumage score improvement overtime (P = 0.04), with rehoming the parrot being the most common and effective, whereas parrots that received no intervention worsened overtime. These findings highlight the importance of the household environment, feed and foraging enrichment on feather-damaging behavior in companion parrots. Scientists should take advantage of the wealth of data available on video sharing websites, especially when interested in understanding the risk factors for behavioral problems in the home environment.

Operating rooms are units of particular interest in hospitals as they constitute more than 40% of total expenses and revenues. Managing operating rooms is challenging due to conflicting priorities and preferences of various stakeholders and the inherent uncertainty of surgery durations. In this study, we consider the next-day scheduling problem of a hospital operating room. Given the list and the sequence of non-identical surgeries to be performed in the next day, one needs to determine the scheduled durations of surgeries where the actual duration of each surgery is uncertain. Our objective is to minimize the weighted sum of expected patient waiting times, room idle time and overtime. First, we provide a reformulation of the objective function in terms of auxiliary functions with a recursive pattern that enables exact analysis of the optimal surgery durations at the expense of high CPU time. Next, we develop and analyze simple-to-use and close-to-optimal scheduling heuristics motivated by practice, for the OR managers to deploy in the field. Our proposed hybrid heuristic attains 1.22% average performance gap and worst average optimality gap of 2.77%. Our solution is easy to implement as it does not require any advanced optimization tool, which is the reality of many operating room environments.

Objective To investigate the 1) socio-demographic characteristics, 2) working environment, 3) tasks and responsibilities and 4) work experiences of intercultural mediators (IMs) working in Belgian hospitals. Methods Cross-sectional quantitative survey among all IMs working in Flemish and Brussels hospitals (n = 66). Data were descriptively analyzed. Meaningful associations between variables were also studied. Results Most IMs are young women from first- and second-generation migrant groups with different levels of education. They work under different superiors and most IMs are not employed full-time. They work mainly with patients from their own ethnic group. Mostly they intervene directly in daily intercultural communication, as per their official task description, but they also perform other tasks, such as offering support to patients/families/staff/management. IMs would prefer more of the tasks they perform to be formalized. Furthermore, they want to have policy-making responsibilities. IMs have positive and negative work experiences, e.g. working overtime. Conclusions IMs’ socio-demographic characteristics (ethnic origin - sex - education) and official task description is only adapted to needs in the workplace to a limited extent. Furthermore, intercultural mediation is poorly integrated into hospitals’ organizational structure. Practice implications Different measures are needed, including tailored education and offering IMs enough organizational support and policy responsibilities.

Taxis are an indispensable part of the public transportation system; however, the industry is confronting many challenges, such as the development of mobile apps for reservations and the increase in large-scale ridesharing. Taxi demand is impacted by many spatial and temporal factors, such as the location, the built environment, the time of day. This study analyzes various factors associated with temporal and spatial densities of taxi pick-up locations using a generalized additive mixed model. The key findings are as follows: (1) taxi demand is higher in densely developed areas, which are characterized by high degrees of mixed land use, high population densities, dense road junctions, and high percentages of residential, commercial and public space; (2) taxi demand is higher in areas with denser secondary roads; (3) taxi demand is lower in areas with more bus stops; (4) taxi demand is higher during weekdays, peak hours, and warmer days (autumn season); and (5) despite taxi demand being positively associated with the rainy season, this relationship has strong nonlinearity. To optimize the efficiency of taxi system, there should be more loading spaces for taxis in activity-concentrated areas, which are characterized by a higher population density, high levels of mixed land use and dense road junctions. In addition, taxi drivers should search for passengers in underserved areas to reach potential passengers during nonpeak hours. Future research may use data recorded via mobile apps to examine taxi overtime waiting, rejection of service and prepaid empty trips to provide a complete image of taxi demand.

Efficient patient scheduling has significant operational, clinical and economical benefits on health care systems by not only increasing the timely access of patients to care but also reducing costs. However, patient scheduling is complex due to, among other aspects, the existence of multiple priority levels, the presence of multiple service requirements, and its stochastic nature. Patient appointment (allocation) scheduling refers to the assignment of specific appointment start times to a set of patients scheduled for a particular day while advance patient scheduling refers to the assignment of future appointment days to patients. These two problems have generally been addressed separately despite each being highly dependent on the form of the other. This paper develops a framework that incorporates stochastic service times into the advance scheduling problem as a first step towards bridging these two problems. In this way, we not only take into account the waiting time until the day of service but also the idle time/overtime of medical resources on the day of service. We first extend the current literature by providing theoretical and numerical results for the case with multi-class, multi-priority patients and deterministic service times. We then adapt the model to incorporate stochastic service times and perform a comprehensive numerical analysis on a number of scenarios, including a practical application. Results suggest that the advance scheduling policies based on deterministic service times cannot be easily improved upon by incorporating stochastic service times, a finding that has important implications for practice and future research on the combined problem.

In the developed industries, it has been demonstrated that the efficient incorporation of Ergonomics in procedures and facilities reduces expenses associated with disability, additional or overtime hours, health care, premiums or incident fines. The Lean tools are complicated and beneficial but it can cause Ergonomics problems with promising modifications. Human wealth, the most significant component in an organisation, often feels the essence of the issues. The objective of this job was to evaluate current science understanding on the effect of implementing Lean manufacturing tools from the point of perspective of Ergonomics in manufacturing sectors. This study informs, based on the literature reviewed, how the incorporation of the ethics of both Lean tools and Ergonomics from the plan stage of the workplace can carry advantage to the safety of the employees and at the same time to increase the power of efficiency improvements. This article as well aims to precede trends and possibilities in this field for upcoming studies.

Few studies have examined the use of hand hygiene interventions among health care personnel and employee absenteeism. To improve the hand hygiene practices of emergency room nurses and technicians, we implemented mandatory use of an automated hand hygiene compliance system. After implementation, we found reductions in employee absenteeism and the number of overtime hours worked by substitute staff. These unanticipated results demonstrate a return on investment that benefits the health of employees.

In this paper, we present a new stochastic mixed-integer linear programming model for the Stochastic Outpatient Procedure Scheduling Problem (SOPSP). In this problem, we schedule a day’s worth of procedures for a single provider, where each procedure has a known type and associated probability distribution of random duration. Our objective is to minimize the expectation of a weighted sum of patient waiting time, provider idling, and clinic overtime. We present computational results to show the size and characteristics of problem instances that can be solved with our model. We also compare this model to other formulations in the literature and analyze them both empirically and theoretically, demonstrating where significant improvements in performance can be gained with our proposed model. This work is motivated by our research on developing scheduling templates for endoscopic procedures at a major medical center. More broadly, however, the SOPSP is a stochastic single-resource sequencing and scheduling problem and therefore has applications both within and outside of healthcare operations.

An outpatient clinic serving two independent demand streams, one representing advance booking requests and the other same-day requests, is considered. Advance requests book their appointments through an electronic booking system for a future day, and same-day requests are served on the day they arise. A compact policy formulation is proposed that incorporates major operational levers suggested in the literature. It combines a slot publication policy, which specifies the pattern under which slots are released to the booking system, with an expediting policy that adjusts the daily workload of advance patients. Relying on a wide range of numerical experiments, a heuristic search method is developed for finding the joint publication and expediting policies, minimizing the cost of overtime slots whilst ensuring a waiting and an access constraint is met. Several managerial insights are derived using a combination of illustrative and real data, highlighting the importance of taking an integrated approach towards the operational levers captured by our policy formulation.

In supply chain safety stock placement models, production lead times are typically considered exogenous; however, in many supply networks, lead times are controllable and should be considered as endogenous variables. This work integrates strategic safety stock placement with subcontracting and overtime planning that can be used to optimize lead times. We formulate the problem of jointly optimizing safety stocks and lead times to minimize production and inventory holding costs, while guaranteeing a customer service level. Using a two-stage supply chain, we analyze the impact of subcontracting and overtime on optimal safety stock placement both analytically and numerically. Our analysis suggests that high usage of subcontracting and overtime tend to decouple safety stocks such that both raw materials and finished goods safety stocks are held. For multistage networks, we derive bounds on decision variables, which are used in a dynamic programming algorithm to solve the integrated problem. Experiments on selected supply chains from publicly available data sets show the value resulting from joint optimization of lead times and safety stocks. The results indicate that the integrated problem leads to greater usage of operational flexibility and shorter lead times as compared to the sequential problem, where lead times are optimized locally. In addition, the value of integration depends on the subcontracting and overtime costs along with the value added at a stage.

This study, which we believe will contribute to more successful transplant processes, was carried out to evaluate the level of job satisfaction among organ transplant coordinators and the difficulties experienced by them.As a cross-sectional study, this research was conducted between July 15, 2018, and August 8, 2018, through the support of the organ transplant coordinators working in the Turkish National Coordination Centre. Sociodemographic characteristics, insititutional difficulties and Minnesota Satisfaction Questonnaire were used for data collection. For the evaluation of the collected data, mean, standard deviation, t test, the Kruskal-Wallis test, and the Pearson and Spearman correlation analyses were used.Forty-eight percent of the organ transplant coordinators in this study experienced difficulties in getting overtime pay, whereas 38.2% experienced difficulties in getting the wages they deserved. A significant difference (P .05) was found between having professional certification and job satisfaction level and between coordination system working unit and job satisfaction level. There was a negative correlation between job and job satisfaction level (P .05).It will be useful to provide the necessary support to overcome the difficulties experienced by transplant coordinators and to increase job satisfaction levels.

In many appointment scheduling systems with multiple providers, customers are assigned appointment times but they are not assigned a specific provider in advance – that is, customers can be seen by any available provider. This type of system is common in a variety of service sectors, such as healthcare, banking, and legal counseling. The majority of the existing literature assumes constant service times or does not consider customer no-shows, which are unrealistic assumptions in many situations. In this paper, we overcome this shortcoming by developing an appointment scheduling model that considers stochastic service times along with customer no-shows for multiple-provider systems with identical providers. The objective is to minimize the weighted sum of customers’ waiting time, and providers’ idle time and overtime. We model this problem as a time-inhomogeneous Discrete-Time Markov Chain process. We use analytical results to reduce the space of optimal schedule candidates, and we employ machine learning techniques to detect patterns among optimal or near-optimal schedules. We then develop an effective heuristic method which provides schedules that perform better than the ones generated by existing models. We test our heuristic both on simulated data and a real-world application. As the real-world application, we collaborate with a local counseling center to implement the schedules suggested by our method. Results from this field experiment reveal an average schedule cost reduction of 16% per day, with a maximum reduction of 40% per day.

Incorporating patient-centered medical home (PCMH) principles, we develop an adaptive appointment scheduling model for a primary care setting. We propose a simulation optimization approach to sequentially schedule appointments to provide desirable schedules from the perspective of both patients and the medical practices. The objective minimizes the weighted expected cost of patient direct and indirect waiting time, physician idle time, and physician overtime. Our efficient data-driven algorithm considers patient preferences and future appointment requests, while employing overbooking to mitigate patient related uncertainties, such as no-shows and lateness. Benchmarking against myopic and optimal algorithms, computational results show that the adaptive scheduling approach provides significant value. The adaptive method provides considerable cost savings even under conditions of high patient uncertainty. In addition, the method produces high quality solutions in little time, thus providing a viable tool for practice.

This research work has two objectives. On the one hand, to analyze the influence that Perceived Usefulness of Programmatic Advertising (PA) has on the user's Concern about Privacy, and on the other, to check whether this relationship changes over time. That is, to find out how improvements in the effectiveness of programmatic advertising might increase the users' concern for privacy. Today, programmatic advertising can be very invasive, not only because of the use of cookies and geolocation, but also because of using algorithms that analyze users' interests in order to offer related products at a later date when the user visits other different websites which are not at all related to the first. Secondly, this document investigates whether this relationship increases over time and if there are any time-related effects. In this study, data from of a very large sample of Internet users in Spain (n = 14,822) was analyzed at three different moments of time between 2013 and 2017. PLS-SEM was used for the analysis given its usefulness in social studies. Several groups were analyzed to test the difference between the path coefficients of the latent variables at different moments in time. Academics and professionals will benefit from this document by being able to see the importance of this relationship over time and how it changes. The use of a longitudinal study allowed for an investigation into, not only the existence of the relationship, but how it changed over the years.

This is the first study that uses microdata to analyze the characteristics of women and workplaces that are associated with the risk of maternity harassment (MH). Existing surveys find that regular employees are more likely to be victimized by MH than are non-regular employees. Using Fairlie’s decomposition method, this study decomposes the regular/non-regular gap in the rate of victimization into such factors as education, tenure, voluntary resignation, pressure to work overtime, clear job description, and male-dominated workplace. I find that voluntary resignation and pressure to work overtime are the two largest factors that explain the regular/non-regular gap in the risk of MH. I also find that organizations that provide clear job descriptions have low risk of MH. The results suggest that organizations could reduce the risk of MH by clarifying individual employees’ roles and by highly evaluating employees who execute their duties without overtime.

Operating Rooms (ORs) are a critical resource in hospitals. Managing ORs efficiently is a difficult task for hospital managers, as patients’ surgery durations have high variability and cannot be accurately predicted in advance. This paper considers a Surgery Block Allocation (SBA) problem, which includes determining the ORs to open and assigning the surgeries in a daily listing to the ORs, towards minimizing the weighted sum of OR opening costs and expected overtime (relative to a fixed length-of-day) penalty costs. Based on real-life surgery durations’ data, we construct an ambiguity set of distribution, which incorporates the empirical means, the mean absolute deviations and the support set. In particular, we help the ambiguity-averse managers develop a distributionally robust model for the SBA problem, where the overtime costs are evaluated over the worst-case probability distribution within the ambiguity set. Bounds on the objective value are discussed. Due to its intractability, we reformulate it as a Mixed Integer Linear Programming (MILP) model using the duality theory. To solve large-scale instances, we employ the linear decision rule technique and develop an approximated MILP model, and propose another approximated MILP model by heuristically constructing a discrete distribution that is “close to” the worst-case distribution. Computational experiments show that our models outperform an existing stochastic programming model in terms of computational time and upper-decile performance. In particular, the heuristic method greatly improves the computational efficiency without pulling down the out-of-sample performances.

In real-world environments, project activities may be performed using multi-skill resources. When both manpower and equipment are needed to perform project activities, wage and energy costs may form the main components of total project cost. Most energy-consuming activities do not need to be performed at specific times, and regarding time-of-use electricity tariffs may be performed during off-peak hours to reduce both energy cost and power peak demand. Performing such activities in off-peak hours obliges employers to pay shift differentials which increases the wage cost. Since energy and wage costs move in opposite directions, a model that optimally schedules activities, such that the total cost (sum of energy and wage costs) is minimized is of particular importance from the demand side viewpoint. The present paper presents a bi-objective optimization model for the multi-skill project scheduling problem considering shift differential payments and time-of-use electricity tariffs, aiming to minimize project total cost and completion time. The proposed model is solved using multi-objective decision making techniques. Results show that taking into account both time-of-use electricity tariffs and regular/overtime payments not only reduces energy cost and total project cost, but also reduces the power peak demand, thereby benefiting power distribution networks as well.

This research work considers the multi-product multi-period capacitated lot-sizing problem with setup times and overtime with backordering allowed (CLSPSTOB) under demand uncertainty by means of a budget-uncertainty set robust optimization. We first present a mixed integer linear programming (MILP) model that describes the deterministic CLSPSTOB with production costs, setup costs, inventory holding costs, backordering costs, and overtime costs. Then, a robust optimization approach is applied to deal with the demand uncertainty with unknown probability distribution, and a robust counterpart model based on duality theory is obtained. Some numerical experiments are presented for the robust capacitated lot-sizing problem with setup times and overtime with backordering allowed (RCLSPSTOB).

We consider the assignment of jobs to heterogeneous agents in a dynamic system with a rolling time horizon. An example is a hospital operating theatre where the jobs are surgeries and the agents are the surgeons. The paper is presented in the context of surgery allocation and the system is characterized as follows: Patients are grouped into categories and they arrive continually following a stochastic process. Patients in each group have specific time limits within which they need treatment and if it cannot be accommodated then the patients are outsourced. The service level is the percentage of patients in each group treated within the time limit. Surgery durations are stochastic and depend on the surgeon conducting the surgeries. Each surgeon has limited time available and expected overtime is penalized by a non-decreasing convex function. We develop a column generation approach for the assignment of already arrived patients and tentative future patients to surgeons on specific days. It balances the conflicting objectives of including as many arrived patients as possible within their time limits, maximizing the service level of future patients, and minimizing the expected overtime of surgeons. A computational study is conducted with the model embedded in a rolling time horizon frame. The study indicates that the assignment of patients based on our model increases system performance in terms of service level and reduced overtime compared to a First-Come-First-Served (FCFS) policy when the arrival rates of patients are medium to high compared to the capacity of the system.

This work studies an employee scheduling problem considering risk aversion under uncertainty demand (i.e., customer traffic) in retailing. Stochastic employee scheduling comprises two stages, the here-and-now decision (i.e., first-stage), before the actual demand is known, is to allocate number of full-time employees to shifts by using some forecast or empirical data; the wait-and-see decision (i.e., second-stage) involving takes some recourse actions, such as recruit part-time employees and extend shift length of full-time employees (i.e, overtime shift), since the actual demand realization. In order to adapt different decision environments, especially facing decision makers with different risk preference, and guarantee scheduling resilience, the risk measure (e.g, conditional value-at-risk (CVaR)) is taken into consideration in the general two-stage stochastic programming framework. A sample average approximation algorithm is used to solve the risk-averse employee scheduling problem with uncertain demand.

The emergent field of sustainable product development has been rapidly evolving in several academic publications. Furthermore, sustainable product development is the basis for innovative products (and services). The analysis begins by identifying published studies within the last five years. A systematic mapping of the field evolution overtime is performed by identifying areas of current research interests and potential directions for future research. The findings will provide a roadmap for further investigations in this field.

We investigate how volume flexibility, defined by a sourcing cost premium beyond a base capacity, at a local responsive supplier impacts the decision to reshore supply. The buyer also has access to a remote supplier that is cheaper with no restrictions to volume flexibility. We show that with unit lead time difference between both suppliers, the optimal dual sourcing policy is a modified dual base-stock policy with three base-stock levels. Fast orders follow a modified base-stock policy with two base-stock levels: the inventory position is raised to the higher base-stock level by using the base capacity; no overtime is used if this order increases the inventory position above the lower base-stock level. Else, the base capacity and overtime are used to raise the inventory position up to the low base-stock level. After ordering from the fast supplier, an order to the slow supplier is placed to raise the inventory position to a third base-stock level. Surprisingly, in contrast to single sourcing with limited volume flexibility, a more complex dual sourcing model results in a “simpler" policy that replaces demand in each period. The latter allows analytical insights into the sourcing split between the responsive and the remote supplier. Our analysis shows how increased volume flexibility at responsive suppliers promotes the decision to reshore operations and effectively serves as a (cost) benefit. It also shows how investing in base capacity or additional volume flexibility act as strategic substitutes.

“Crunch”— the cyclical labor practice used to ensure delivery of content for commercial release within a certain time frame—is an unregulated and unconscionable convention. While common in a variety of industries, it is particularly disruptive in, and the root cause for, many of the video game industry’s shortcomings. Crunch in the video game industry is most commonly comprised of excessive, and often lengthy, durations of mandatory unpaid-overtime hours and an unspoken stigma for any who condemn a studio’s policies on a rushed production. Video game crunch is a direct result of the limited labor protections currently afforded to individuals within the industry and the rapid expansion of video games as a form of mainstream entertainment globally. Thus far, only one other scholarly article addresses the labor concerns facing the video game industry, and that article has a very narrow focus on how a recent development in California’s approach for classifying an individuals’ employment status would affect the video game workforce’s ability to unionize in that state. Currently, there is no other academic literature specifically addressing crunch labor conditions, and my Article fills this substantial gap by providing readers with a much broader analysis of the issues. This Article provides a general background into the rise of the video game industry into a global phenomenon and a detailed understanding of what crunch entails to capture the significance of its consequences. It then provides an analysis of the relevant federal and state labor provisions for which any redress must be relied upon. As Texas is the second-largest hub for video game development in the United States and its industry reach is growing in response to the economic incentives provided by Governor Abbott, this Article takes a targeted approach for addressing the industry-wide problem. This Article advocates against the use of unionization as a means of redress for the industry’s workforce, arguing it would be largely ineffective given the current state of the industry. This Article alternatively advocates for Texas to pass the substantive provisions of a labor act developed in the Article in order to address the core issues behind crunch. Specifically, this Article argues that the Texas state legislature should be tasked with expanding upon the minimum labor protections already afforded to its citizens by the federal Fair Labor Standards Act by passing provisions that include the following: (I) limiting the amount of overtime that can be mandated from an individual, (2) introducing the applicability of overtime pay provisions beyond who is currently considered under the Fair Labor Standards Act, and (3) expanding anti-retaliation provisions beyond internal complaints from an individual. The State must make this legislative push. Without it there will be no sustainable path for unionization to become a viable option for approaching labor concerns in the industry’s future. The economic benefits provided to the State by the success of this industry and the Texas legislature’s worker-centric ideology warrant this moderate legislative intervention.

Highlights • Incorporating data on daily Google searches, we investigated whether COVID-19 mitigation policies were associated with symptoms of depression and anxiety. • We found that mitigation policies were positively associated with the search indexes for mental health symptoms but do not suggest durable effects. • Moreover, the policies decreased searches for antidepressants and suicide, revealing no evidence of increases in severe symptomatology. • We found suggestive evidence that the policies increased within-home hours which might promote new routines and greater social support within the family., Given the unprecedented level and duration of mitigation policies during the 2020 COVID-19 pandemic, it is not surprising that the public and the media have raised important questions about the potential for negative mental health consequences of the measures. To answer them, natural variability in policy implementation across US states and over time was analyzed to determine if mitigation policies correlated with Google searches for terms associated with symptoms of depression and anxiety. Findings indicated that restaurant/bar limits and stay-at-home orders correlated with immediate increases in searches for isolation and worry but the effects tapered off two to four weeks after their respective peaks. Moreover, the policies correlated with a reduction in searches for antidepressants and suicide, thus revealing no evidence of increases in severe symptomatology. The policy implications of these findings are discussed.

The legal identity of on-demand platform workers has become a central site of conflict between labor and industry. Amidst growing economic inequality, labor representatives and workers have demanded that platform workers be afforded employee benefits and protections, including minimum wage and overtime rights. Platform industrialists, meanwhile, have proffered a new regulatory category of worker—neither employee nor independent contractor—that limits the protections available to the workforce, legalizes unpredictable, digitally-personalized piece-pay, and constricts a worker’s right to negotiate different terms. To date, legal and socio-legal scholars have primarily analyzed this third category of worker, codified by Proposition 22 in the state of California, in race-neutral terms. In this Article, I make visible the racial politics of this tiered system of worker protection. Using historical, legal, and ethnographic methodologies, I argue that the wage system created by Prop 22 and the third category of worker has been both rationalized (by industry) and contested (by labor) through a recognition of systemic racial inequalities. Adopting the language of racial justice, platform employers justified the elimination of pay for all time spent laboring and other worker protections as a means of providing economic opportunities to struggling immigrants and racial minorities. Workers, however, argued that the corporate recognition of racial inequality strategically neutralized political support for employment protections, including the minimum wage, thereby remaking racialized economic hierarchies and undermining labor solidarity. Drawing on historical comparisons made by platform workers campaigning against Prop 22, Part I situate the third category of worker within a genealogy of industry-sponsored racial wage codes, proposals, and debates during the First and Second New Deals. In Part II, I argue that companies supporting Prop 22, like their early twentieth century counterparts, strategically used race as a resource to eliminate access to employment protections. Finally, in Part III, I analyze how platform workers who collectively fought the passage of Prop 22 rejected the rhetorical liberalism of their employers and examine their actions and visions for a path to racial and economic justice. Building on the workers’ analyses and actions, I argue that facially neutral employment and labor rights carve-outs for the gig workforce are made possible by and reproduce racial subjugation. As the platform companies attempt to spread their Prop 22 wage model in other locales, lawmakers and labor representatives shaping or re-defining minimum employment standards must consider the racialized consequences of this formative reality.

To what extent do US firms have an incentive to comply with the Fair Labor Standards Act (FLSA) and the National Labor Relations Act (NLRA)? I examine this question through a simple comparison of the expected costs of noncompliance (in terms of legal sanctions) to the profits firms can earn through noncompliance. In the case of the FLSA minimum wage and overtime provisions, typical willful violators are required to pay back wages owed and in some cases additional penalties, if detected by the Department of Labor (DOL). Based on available data on the penalties levied, a typical firm would need to expect a chance of at least 78–88 percent that its violation would be detected in order to have an incentive to comply with the FLSA. In practice, the probability of detection many firms can expect to face is likely much lower than this. In the case of the NLRA, a firm that fires a worker illegally is required to reinstate the worker with back pay if the violation is detected. Based on empirical estimates of the effect of unionization on firm profits, a typical firm may have an incentive to fire a worker illegally for union activities if this illegal firing would reduce the likelihood of unionization at the firm by as little as 0.15–2 percent. These analyses illustrate that neither the FLSA nor the NLRA penalty and enforcement regimes create sufficient incentive to comply for many firms. In this context, the substantial evidence of minimum wage and overtime violations, and of illegal employer behavior toward unions, is not surprising.

A worker’s classification as either independent contractor or employee drives whether a worker is entitled to minimum wage, overtime, worker’s compensation, unemployment compensation, anti-discrimination protection, NLRA protections, and many other safety-net protections. During COVID-19, unemployment protections were extended to independent contractors, but this is not the norm and likely will not continue post-pandemic. Classifying certain workers, particularly those who work in the gig economy, is challenging, so states are looking for an answer – either through their own innovation or through that of other states. California’s answer was AB5. AB5’s goals were to correct misclassification issues for app-based drivers and other workers. A plethora of workers including court reporters, freelance writers and photographers, coaches, truckers, performing artists (mimes, magicians, comedians, etc.), and musicians rebuked AB5. AB5 is well known beyond California’s borders as it received, and continues to receive, nationwide attention because it reclassified app-based drivers (such as Uber, Lyft, DoorDash, etc.) as employees. This reclassification was ineffectual because Uber’s Prop 22 passed in November 2020 rendering app-based drivers exempt from California’s worker classification law. As Justice Brandeis said, one of the benefits of federalism is that states can act as “laboratories of democracy.” Experimental federalism can provide for collective learning across the states if they are all experimenting, but often states look to one another for innovative solutions so that they can free-ride instead of experiment. Some states that are looking for an improved worker classification law seek to learn from, and potentially free-ride on, California’s AB5 “experiment.” In considering whether to adopt AB5 or a similar statute, states should consider, at a minimum, three factors: relevancy of the law to their state, ease in obtaining information about the law, and the costs to adopt, implement, and enforce the law. This article assists policymakers and interest groups by providing a detailed look at the AB5 experiment including the impact of Uber’s Prop 22. This article applies the aforementioned three factors and determines that California’s law, while well-intentioned is likely not valuable for, or adoptable by, other states or the federal government partly because it contains 109 exemptions. Ultimately, this article concludes that to maximize the benefits of experimental federalism, a group of states, both homogenous and heterogenous to California, should experiment with more novel approaches to reach a more optimal solution to worker (mis)classification. Adopting California’s worker classification law will result in states following a sub-optimal law and delay states from reaching a better solution. Workers need protections, but California’s worker classification law does not sufficiently satisfy this need.

We calibrate to the Brazilian economy a model of means of payment choice, where households have different preferences over anonymity. Financial sector is monopolistically competitive and may break the link between borrowing and lending rates. A sufficiently attractive digital currency reduces holdings of both cash and bank deposits. Since cash use is costly, the digital currency may increase welfare. However, if banks are liquidity constrained, the digital currency may result in less loans and output, and then reduce welfare. The digital currency interest remuneration can be set and be adjusted overtime to optimally balance this trade-off.

If an employer can take away the right of “acting together” from its employees and force them to proceed only “individually” to enforce rights related to their wages and other terms and conditions of employment, the employer has interfered with or restrained the “collective power of individuals” that Alexis de Tocqueville observed in Democracy in America. The Norris-LaGuardia Act of 1932, the National Labor Relations Act of 1935, and the Fair Labor Standards Act of 1938 are all New Deal era statutes – all of which are still in force today – which provide for the right of employees to proceed collectively or in concert. These statutes were the culmination of decades of struggle in workplaces and communities, state and federal legislatures, and state and federal courtrooms. Each rests on detailed Congressional findings that individual employees do not “commonly” enjoy “actual liberty of contract” or “full freedom of association” and have an “inequality in bargaining power” vis a vis the employer, and that “collective” actions to resolve disputes over the terms and conditions of employment are in the interest of employees and the public. And while it is rarely noticed today, from 1923 to 1925, the Supreme Court issued three unanimous decisions on the unconstitutionality of “compulsory arbitration,” holding that compulsory arbitration implicates the due process and liberty of contract protected by the Fourteenth Amendment, except in temporary emergencies. See, e.g., Charles Wolff Packing Co. v. Court of Indus. Rel., 267 U.S. 552, 565-66 (1925). In Epic Systems Corp. v. Lewis, 138 S.Ct. 1612, 1624-25 (2018), a 5-4 majority opinion, written by the then-new Justice Neil Gorsuch, upheld compulsory arbitration agreements with “class action waivers” in three companion cases, even though the waivers clearly constituted unbargained-for restraints on the collective enforcement action provided in Section 16(b) of the Fair Labor Standards Act. All of the cases involved the right to receive overtime pay, which applies even when employees earn more than the minimum wage. In upholding the class/collective action waivers, the majority opinion in Epic displayed a near total ignorance of class and representative actions in “the old, nearly forgotten world before 1966," Elizabeth K. Spahn, “Resurrecting the Spurious Class,” 71 Geo. L.J. 119, 120 (1982). It also displayed a woeful ignorance of the history of the use of “liberty of contract” theories to block the enforcement of wage and hour standards, and Congress’ rejection of those theories in the legislative findings and declarations of policies of the New Deal legislation.

The conventional 40-hour workweek has been a fixture of the American workplace for almost a century. Standard working hours of nine-to-five, Monday-to-Friday, are customary even for workers exempted from overtime under the federal Fair Labor Standards Act of 1938 (FLSA). But the traditional 40-hour workweek is no longer a fit for the modern family or the modern worker. It is time for its demise. In the decades since passage of the FLSA, the influx of women in the workforce and the growth of exempt knowledge work have rendered the traditional 40-hour workweek both needlessly restrictive, in the case of work-life conflict, and effectively meaningless, in the case of the information age worker who labors 24/7. The recent revolution in remote work, precipitated by the COVID-19 pandemic, auspiciously permits a new approach to working hours, especially for exempt, “remote-ready” workers—that is, white-collar workers engaged in cognitive labor, who have the proven capacity to work offsite. Where exempt, remote-ready workers are already widely expected to work outside of so-called office hours, they should not be beholden to keep regular office hours, too. We should release them from the false confines of nine-to-five, for more fluid integration of work and life. By amending the FLSA regulations to make scheduling freedom a condition of white-collar exemption, and restricting employers from setting hours of work for this cohort, we could productively disrupt the outdated workweek for all.

The stability of financial institutions in coordinating and navigating the affairs of a nation’s economy is considered as a bedrock of economic development for any nation. The need to create an efficient financial system anchored on financial stability and effectiveness has become more imperative overtime in order to ensure economic growth. There is also the imminent need for financial institutions (Traditional and non-traditional financial institutions) to acclimatize to the trends of financial digitalization across the globe. The Central Bank of Nigeria (CBN) and the NDIC (Nigeria Deposit Insurance Corporation) are two financial bodies ladened with the responsibility of overseeing and managing the system of banking in Nigeria. This paper seeks to examine the roles of these two financial bodies in Nigeria in ensuring financial stability in the country’s economy.

This study provides a new perspective regarding the potential benefits of combining three different labor flex ibility strategies to solve an annual staffing problem. These labor flexibility strategies are as follows: (i) annu alized hours, which allows an irregular distribution (e.g., weekly, monthly) of an annual number of working hours per employee hired; (ii) multiskilling with 2-chaining, which involves employees being trained to work on up to two task types, so that the training structures form closed chains; and (iii) overtime. A mixed integer linear programming model is proposed to determine how many employees will be hired, how many of them will be multiskilled and in what task types, and how will be the weekly allocation of ordinary and overtime hours for each employee type (single-skilled or multiskilled) according to the agreed annualized hours contract. For a case study in the Chilean retail industry, the results showed that the proposed triple labor flexibility strategy reported greater savings in total cost compared to the single or double flexibility strategies. The results also indicated that multiskilling and overtime are complementary sources of flexibility under an annualized hours contract. In fact, for different store sizes, patterns of seasonality in demand and levels of variability in demand, the proposed strategy achieves close to 100% coverage in demand and over/understaffing levels of approximately 0%.

Work hours and scheduling matter for the well-being of those employed throughout the state in Illinois, perhaps now more than ever. Before Chicago implemented the Fair Workweek ordinance (FWW) in July 2020, we issued a large-scale, geographically, and demographically representative survey of workers throughout Illinois, at the end of 2019, of over 3,000 employed. This survey provides a portrait of at least eight dimensions of work hours and schedules, their distribution by type of job and worker and across 23 different industries - those covered by Chicago’s ordinance and those uncovered. It tests empirically for their association with five indicators of workers’ well-being by focusing on: Wanting more hours (underemployment, hours inadequacy); Least to most hours worked (variability or instability); Irregular shift times; On-call work; Short advance notice of schedule; Schedules set by employer with little to no input from workers; Schedules changing after posting; and Overtime hours that are mandatory.

COVID-19 is a highly contagious disease and has been spread to most countries of the world with unprecedented transmission speed. Medical resources and treatments provided by the healthcare system are most critical to reduce the mortality rate of COVID-19 and to contain the spread of COVID-19 by isolating infectious individuals. We introduce a modified SEIR model with consideration of individuals’ access to limited medical resources to characterize the vital role of critical medical resources during the pandemic. We discuss how the three different hospital admission policies (hierarchy, mixed, and Fangcang sheltered healthcare system) affect the spread of the disease and the number of deaths and infections. We find that Fangcang shelter system results in the least number of infections, deaths as well as occupied beds among all three systems. In addition, when the hospital capacity is relatively high or transmission rate of the mildly infected patient is not ignorable, a mixed system can result in a lower number of infections and deaths but higher occupied beds than a hierarchy system because it prevents the disease transmission to a great extent. Public policies of social distancing play an important role in moderating the spreads overtime. We investigate the performance of the three healthcare systems under a static social distancing policy. We find that, under a static social distancing policy, a Fangcang shelter system results in the largest reduction in infections and deaths. Moreover, we conduct simulations on two types of dynamic lockdown policies and find that an effective dynamic lockdown policy should smooth the burden of a healthcare system and keeping minimum disruption of economic activities. That is, a lockdown that occurs either too early or two late could result in more deaths and infections.

This paper studies how former interest groups’ employees turned politicians (who we label as lobbyist legislators) influence the voting behavior of their colleague legislators. Using the alphabetic allocation of seats in the European Parliament and detailed individual resume information, we find that legislators connected to lobbyist legislators are 7% more likely to coincide in their ballot with that of the lobbyist legislator only when the subject of the vote is deemed of importance to the interest group’s economic activity. Lobbyist legislators are influencing their connections’ ballots by achieving a 44% reduction in voting abstention. Lobbyist legislators substantially increase the likelihood of their connections casting their same ballot during high-stakes votes, however legislators slowly learn from their connections’ leanings and preferences, and tend to deviate overtime. All the effects are similar in size to that of being connected to lead legislators responsible for calling the party’s position in each motion.

It is widely explored that problems in developing society related to think and act logically and reflectively in a social context positively correlates with the cognition skill. In most developing societies, people are busy with problems that they face daily (i.e. working overtime), limits their cognitive capacity to properly process a social stimulus, which mostly asked their thoughtful response. Thus, a better design in social stimulus to tackle problematic behaviour, such as littering, to name a few, becomes more prominent. During the last decade, nudge has been famous for its subtle approach for behaviour change – however, there is relatively little known of the method applied in the developing society. The current article reviews the nudge approach to change human behaviour from two perspectives: cognitive science and consumer psychology. The article concludes that intervention using the nudge approach could be beneficial for current problematic behaviour.

How do public sector workers balance pro-social motivations with private interests? In this study of police officers, an arrest often requires working overtime. We document two consequences to officer behavior. First, contrary to popular wisdom, officers reduce arrests near the end of their shift, and the quality of arrests increases. Second, officers further reduce late-shift arrests on days in which they “moonlight” after work. Using these results, we estimate a dynamic model that identifies officers’ implied tradeoff between private and pro-social motivations. Incentives created by overtime pay are insufficiently large to change police decision-making at the margin.

The paper presents an alternative incentive scheme to overcome some of the challenges posed by usual kind of pay-for-performance employee wage contracts offered by the firms.

Overtime, corporate social responsibility has morphed from being perceived as an irrelevant concept outside corporate governance, to being recognized as a core organizational objective. In the contemporary business world, managers employ the concept as a strategic tool for compliance with regulations and the maintenance of standards. The concept of corporate social responsibility is also liked to company reputation and has for a long time commanded consumer loyalty. However, there are still debates as to the place of corporate social responsibility and whether indeed it is a subset of corporate governance. In order to determine this, it is imperative to first get a more nuanced understanding of the concept. This paper attempts to unravel the ontology of corporate social responsibility in corporate governance by tracing its historical origins, its development and its role in corporate governance. This chapter also delves into the legal aspects of corporate social responsibility, its role and significance, emerging global trends and challenges to corporate social responsibility.